Quantum Computing Research Archive

Yuval Boger interviews Mehmet Sanliol, managing director at Evercore covering quantum technologies and semiconductors. They discuss how investors value public quantum companies, when private companies should consider IPOs or SPACs, and why consolidation may shape the next phase of the industry. Mehmet also shares his perspective on technical and market signals that could affect valuations, the outlook for quantum software, and the recent developments in quantum that caught his attention most. Transcript Yuval:  Hello, Mehmet, and thank you for joining me today. Mehmet:  How are you, Yuval? My pleasure. Yuval:  So, who are you and what do you do? Mehmet:  So, my name is Mehmet Sanliol. I am the managing director at an investment bank called Evercore, and I focus on quantum technologies and semiconductors. Yuval:  So, why don’t I start from the end? So if you’re speaking with the CEO of a private quantum computer company, one that has delivered the product, has investors, has some good technical progress, what would you advise them to do about the public markets? Mehmet:  So the way that, look, you’ve seen a number of companies, I think we’re now up to kind of seven and having entered the public markets. Thankfully, all seem to be trading well enough so far. And the older companies are kind of well in excess of the $10 stock price and the few others that have joined are hovering around that level. I really think about it as a de-risking strategy because access in the public markets does provide you with the ability to tap liquidity in a manner that’s not necessarily always going to be available on the private side. You do open yourself up to public scrutiny and at some point you see some of the companies that had been traded for a few years now from kind of ’21 onwards go through some tough times and you really need to kind of weigh those two things against each other. To my mind if you are already full

Abstract Fast electrical spin rotations in quantum dots require strong spin-charge hybridization, but the same hybridization can increase sensitivity to detuning noise. In a double-quantum-dot (DQD) flopping-mode qubit, the sweet-spot width and the Rabi enhancement are both tied to the same orbital splitting, limiting post-fabrication optimization of the speed-coherence trade-off. Here, we demonstrate a GaAs triple-quantum-dot (TQD) flopping-mode qubit in which the detuning of the third dot, ϵ 34 , provides an additional electrical tuning parameter for orbital-band flattening. Tuning ϵ 34 flattens the qubit-frequency dependence on the detuning of the target DQD while maintaining strong spin-charge hybridization, enabling electrically driven Rabi frequencies above 100 MHz. We then use feedforward-neural-network (FNN) feedback to track slow qubit-frequency drift and connect this engineered operating point to high-fidelity gates. This feedback suppresses slow qubit-frequency fluctuations, reducing their standard deviation to 388 kHz, and yields a π /2 gate fidelity of 99.56% with a 4.05 ns gate time. These results identify TQD orbital-band engineering as an electrical route for tuning the speed-coherence trade-off, complementary to material-intrinsic spin-orbit coupling and fixed micromagnet geometry.

Inteli, a Brazilian higher education institute, has become an accredited ICT and partnered with IBM Quantum. This collaboration grants Inteli researchers cloud access to IBM Quantum systems to explore quantum algorithms for decision-making under uncertainty, with a focus on practical industrial applications in Latin America. The partnership aims to advance quantum computing capabilities and workforce development in the region. The post Brazil’s Inteli Becomes Accredited ICT and Partners with IBM Quantum to Research Decision-Making Under Uncertainty appeared first on Quantum Computing Report .

What would it take to watch an electron move through a material? Researchers would need to see individual atoms and capture an electron's motion at incredibly short timescales. A Technion-led team has brought those two capabilities together in a scanning tunneling microscope, using carefully shaped laser pulses to control the direction of electron flow while preserving nanoscale spatial resolution.

Iceberg Quantum's Pinnacle 1.2 architecture, featuring the Crevasse QLDPC decoder, significantly reduces the resources needed to factor RSA-2048. They achieved logical error rates below 10^-12 per logical qubit-cycle, a critical threshold for this task, through direct circuit-level simulations. This breakthrough could factor RSA-2048 in as little as 0.98 days with 48,000 physical qubits. The post Iceberg Quantum Validates Pinnacle 1.2 Architecture with Crevasse QLDPC Decoder to Reduce RSA-2048 Factoring Resources appeared first on Quantum Computing Report .

Insider Brief Quanova has selected Quandela ’s MosaiQ photonic system for a program at Quang Trung University that the partners say will deploy Vietnam’s first quantum computer. Supported by Nam A Bank, the initiative includes faculty training, dedicated curricula, software access, a Quantum Experience Center and technology events. The partnership will establish a Quantum Innovator Residency Program to develop local expertise and support quantum education, research and entrepreneurship. PRESS RELEASE — Quandela , a European leader in photonic quantum computing, announces a major milestone in its expansion in Southeast Asia. Quanova, a Vietnamese quantum company, has selected Quandela ’s MosaiQ solution as the foundation of a new quantum research, innovation, service and entrepreneurship (quantum-RISE) program at Quang Trung University (QTU) in Quy Nhơn, Gia Lai. The project marks the first France–Vietnam collaboration in quantum computing and will lead to the deployment of Vietnam’s first quantum computer, with the support of Nam A Bank. Vietnam’s first quantum computer at the heart of a strategic education and research program This long-term partnership, developed with Quanova, Quandela ’s strategic local partner in Vietnam, will provide Quang Trung University with a comprehensive platform for education, research and innovation. Nam A Bank is supporting the initiative as part of its commitment to advanced technologies. As Võ Hoàng Hải, Deputy CEO of Nam A Bank, explained: “Nam A Bank invests in core technologies, including quantum technology, to help build high-tech capabilities in Vietnam through strong and effective cooperation with French organizations.” The program includes: Deployment of the MosaiQ photonic quantum computer; Faculty training and development of dedicated curricula; Provision of the software suite and support for the creation of a Quantum Experience Center and launch of the Quantum Innovator Residency Program; Organization of technology ev

Quantinuum and Oracle have launched the OCI Quantum AI Compute Beta Program, offering early cloud-based access to Quantinuum's Helios quantum processor for hybrid quantum-AI workflows. This program integrates Helios within Oracle Cloud Infrastructure (OCI) AI data centers, providing a browser-based Python development environment for various applications. The initiative will be further detailed at Oracle AI World 2026. The post Quantinuum and Oracle Launch OCI Quantum AI Compute Beta Program for Early Access to Helios appeared first on Quantum Computing Report .

Insider Brief Telefónica and IQM Quantum Computers plan to install the first quantum computer in Spain’s Community of Madrid at the Technical University of Madrid (UPM) before the end of 2026. The IQM Spark system is designed for research, education and early-stage development, giving universities, hospitals, research centers and start-ups access to quantum hardware. The project aims to build regional expertise, support the development of industry use cases and expand Madrid’s role in Europe’s quantum technology ecosystem. PRESS RELEASE — Telefónica and IQM Quantum Computers, a global leader in superconducting quantum computing, have joined forces to deploy the first quantum computer in the Community of Madrid. The initiative will strengthen the region’s scientific and technological capabilities, while driving the development of real-world cases for companies across the Community of Madrid. The IQM Spark quantum computer, an all-in-one solution specifically designed for research, education and early-stage development, will be installed at the Technical University of Madrid (UPM) before the end of 2026. It will enable universities, hospitals, research centers and start-ups, direct access to real quantum hardware to develop and test quantum algorithms and build the expertise needed to explore future use cases. This will be the first quantum computer of its kind in the Community of Madrid, significantly increasing the region’s capacity to develop quantum capabilities locally and through hands-on experience. The computer will join the other two quantum computers provided by Telefónica and IQM to CESGA (Galician Supercomputing Centre). Once the new quantum computer is operational, the Community of Madrid will have greater capabilities to foster the creation of its own quantum ecosystem, bringing together all stakeholders involved in developing real-world use cases that deliver direct benefits to local industry. This ecosystem will help attract talent and strengthen

Researchers at AIST have directly observed magnetic flux quanta generated in a superconductor by photon absorption and demonstrated a new principle of photon detection that identifies the number of photons based on the number of these flux quanta.

Chalmers University of Technology has developed TRIO pulses, a new quantum control framework for superconducting processors. These pulses enable single-qubit gates to maintain high fidelity even with significant control-amplitude miscalibrations and frequency detuning errors. This breakthrough offers a way to reduce recalibration overheads in large-scale quantum processors and has been demonstrated with an X-gate achieving 99.90% fidelity. The post Chalmers University Demonstrates TRIO Pulses for Control-Error-Robust Single-Qubit Gates in Superconducting Processors appeared first on Quantum Computing Report .

IQM Quantum Computers and NVIDIA have successfully automated the calibration of a 20-qubit quantum processor using NVIDIA Ising Vision-Language Models (VLMs). This agentic AI system analyzes experimental data, autonomously adjusts parameters, and generates diagnostic logs for human review. They also released QCalEval, an open benchmark for AI-driven quantum processor bring-up, where NVIDIA Ising Calibration models outperformed general-purpose VLMs. The post IQM and NVIDIA Automate 20-Qubit Chip Calibration via NVIDIA Ising Vision-Language Models and QCalEval Benchmark appeared first on Quantum Computing Report .

Insider Brief Google Quantum AI launched a $150,000 Kaggle competition to develop smaller, more efficient quantum circuits for calculations related to fusion energy, optimization and chemistry. Participants will reduce qubit and gate counts while meeting accuracy requirements, potentially lowering the hardware demands of useful quantum algorithms. The competition uses Google ’s open-source kickmix software to efficiently test circuit designs on conventional computers, providing confidence in approximate correctness without proving exact equivalence. Google Quantum AI is launching a competition to use artificial intelligence to shrink the circuits needed for useful quantum computing. The competition offers a total prize pool of $150,000, organizers said. The competition, hosted on Kaggle , challenges participants to reduce the number of computing steps and quantum bits required for tasks related to fusion energy, mathematical optimization and chemistry. Google is providing starting circuits and software to check whether proposed improvements produce sufficiently accurate results. The effort targets a central obstacle to practical quantum computing. Even as researchers build more capable processors, many potentially useful calculations remain too demanding for available hardware. Reducing the work required by an algorithm could lower the hardware requirements for running it. According to Google’s announcement , the competition draws on a method that allows conventional computers to efficiently test a particular class of quantum circuits. That creates a way for AI systems to repeatedly propose changes, check their accuracy and search for further savings. Reducing the Cost of a Calculation A quantum circuit is a sequence of operations used to carry out a calculation. Those operations, called gates, act on qubits, the basic units of quantum information. Current processors have limited numbers of qubits, and their gates can introduce errors. Quantum error correction is de

Guest Post by Liam Wang COO, Logical Qubit Technology. The World Economic Forum’s Quantum Economy Day 2026 was held in Geneva, Switzerland, on October 13–14. Logical Qubit Technology attended as the only quantum computing company representing China. The company’s Chief Operating Officer, Liam Wang, joined business executives, researchers, and representatives of international organizations from around the world to discuss the global development of quantum computing. This June, I took part in a World Economic Forum discussion on global quantum science and technology development at the Summer Davos meeting in Dalian. Representing the company again at Quantum Economy Day 2026 in Geneva gave me a close-up view of how quantum computing is developing in other countries and regions. What Is Everyone Talking About? My first and most immediate impression: China and other countries share many of the same concerns about this industry — how to persuade policymakers, capital, and industry to commit more resources to quantum computing; which application scenarios will see the first breakthroughs; how geopolitics continues to shape the global industry (supply chain security, the setting of global quantum standards, and so on); how to broaden quantum computing’s social reach, steadily moving beyond academia into industry and the wider public; and how the convergence of quantum computing and AI will unfold, and what major opportunities that super-cycle will create. Although the industry is still at an early stage, the overall mood among participants was optimistic . AI was the most common point of comparison: since ChatGPT launched in November 2022, the pace of progress in large AI models has exceeded almost everyone’s expectations. Quantum computing is likely to follow a similar logic. Of course, at this stage, quantum computing still has to be viewed pragmatically. Two terms came up most frequently in the discussions: “use case” and “geopol

Florida Atlantic University received a nearly $400,000 NSF grant to advance post-quantum cryptographic protocols. Led by Dr. Edoardo Persichetti and Dr. Veronika Kuchta, the project will develop advanced functionalities beyond basic primitives to secure decentralized systems against future quantum attacks. The initiative also supports student mentoring and cybersecurity outreach, building on FAU's leadership in quantum-safe security. The post Florida Atlantic University Awarded $400,000 NSF Grant to Expand Post-Quantum Cryptographic Protocols appeared first on Quantum Computing Report .

Leiden University and Riverlane research uncovered a flaw in correlated decoding, causing a loss of effective code distance and higher logical failure rates in quantum error correction. They introduced a new regularization parameter to fix this, restoring nominal distance scaling and improving accuracy without adding computational overhead. This discovery offers a crucial design principle for future quantum decoding architectures. The post Leiden University and Riverlane Research Reveals Distance-Losing Flaw in Correlated Decoding Below Threshold appeared first on Quantum Computing Report .

IBM Quantum has released Qiskit SDK v2.6, significantly enhancing its C API layer with a new pass-manager framework and native QPY serialization. This update allows for custom compiler passes and hardware-native quantum operations in C, C++, and Julia without a Python runtime, moving towards Python-optional execution in high-performance computing. The release also updates the Qiskit GitHub Roadmap, outlining future versions that will focus on C ABI/API stability, fault-tolerant compilation, and a Rust-native execution interface. The post IBM Releases Qiskit SDK v2.6 with C API Pass-Manager Framework, Native QPY Serialization, and Custom Operations appeared first on Quantum Computing Report .

NVIDIA has invested in Riverlane to advance real-time quantum error correction (QEC) and GPU decoder calibration. This collaboration utilizes NVIDIA H100 GPUs to accelerate Riverlane's Local Clustering Decoder (LCD), significantly reducing the time for surface code training cycles and enabling dynamic recalibration of QEC decoders. This advancement helps mitigate qubit drift and hardware defects, paving the way for more stable and reliable fault-tolerant quantum computing systems. The post NVIDIA Takes Strategic Stake in Riverlane to Accelerate Real-Time Quantum Error Correction and GPU Decoder Calibration appeared first on Quantum Computing Report .

Insider Brief A state-commissioned study ranks New York second nationally in quantum-related businesses, research groups and patents, identifying greater coordination as an opportunity to accelerate commercialization. New York has committed $360 million to quantum development, including $300 million for a Stony Brook research hub and $60 million for up to four regional commercialization hubs. The study estimates these investments could support $2.3 billion to $5 billion in economic activity and 7,200 to 10,100 job-years through 2036. PRESS RELEASE — Governor Kathy Hochul today announced the release of a comprehensive study of New York State’s quantum technology landscape, finding that the Empire State ranks second nationally in quantum-related businesses, research groups and patents. Commissioned by Empire State Development’s Division of Science, Technology and Innovation (NYSTAR), the study highlights New York’s position as a national leader in the emerging industry and identifies opportunities to strengthen collaboration, accelerate commercialization and support future economic growth. “New York is building the foundation for the next generation of technological breakthroughs, and quantum technology represents an enormous opportunity for our economy,” Governor Hochul said. “With world-class research institutions, advanced manufacturing capabilities and a growing network of innovative businesses, we have the tools to lead this emerging industry. Our $360 million investment will help turn that potential into progress, bringing new technologies to market, attracting private investment and creating good-paying jobs across New York State.” Empire State Development President, CEO and Commissioner Hope Knight said, “Under Governor Hochul’s leadership, New York is making strategic investments to lead the next generation of technological innovation. This study confirms that our state has the research institutions, manufacturing capabilities and industry expertise nee

Google Quantum AI has launched a $150,000 Kaggle competition running from October 22, 2026, to January 20, 2027. The competition challenges participants to use AI agents to compress fault-tolerant quantum circuits, focusing on "kickmix" circuits which are verifiable by classical computers. This initiative aims to optimize quantum algorithms for applications in fusion energy, optimization, and quantum chemistry. The post Google Quantum AI Launches $150K Kaggle Competition to Compress Fault-Tolerant Quantum Circuits Using AI Agents appeared first on Quantum Computing Report .

Quantum systems can occupy superpositions, quantum states that combine different possibilities. For instance, a microwave field can be prepared in a superposition of an empty state and a state that contains microwave light.

Periodically driven quantum systems exhibit many fascinating phenomena absent in equilibrium systems, but their simulation is more challenging than that of static systems. Consequently, quantum simulation of these systems offers greater opportunity for achieving quantum advantage. To build the foundation for simulating time-periodic Hamiltonians, we utilize the Floquet-Hilbert space formalism to transform the Hamiltonian into a time-independent form and provide its Pauli decomposition. Within this formalism, we develop a hybrid quantum-classical algorithm, Floquet-ADAPT-VQE, that produces three key quantities that govern periodically driven quantum dynamics: the quasienergy, the associated Floquet eigenstates, and expectation values of observables with respect to these eigenstates. The latter is achieved by applying a fixed-depth quantum circuit to an initial Floquet eigenstate—an efficient construction made possible by the Floquet-Hilbert space formalism. We also identify a suitable auxiliary initial state whose squared Floquet energy is independent of the number of auxiliary qubits as well as the driving frequency, which leads to better convergence with fewer ADAPT iterations. We demonstrate our algorithm by performing numerical simulations on a periodically driven XYZ model with a magnetic field. We also explore potential applications of our algorithm for studying various non-equilibrium phenomena in periodically driven systems.

Abstract We propose a Trace-distance binary Tree AdaBoost (TTA) multi-class quantum classifier, a practical pipeline for quantum multi-class classification that combines quantum-aware reductions with ensemble learning to improve trainability and resource efficiency. TTA builds a hierarchical binary tree by choosing, at each internal node, the bipartition that {heuristically} maximizes the trace distance between average quantum states; each node trains a binary AdaBoost ensemble of shallow variational quantum base learners. By confining intrinsically hard, small trace distance distinctions to small node-specific datasets and combining weak shallow learners via AdaBoost, TTA distributes capacity across many small submodels rather than one deep circuit, mitigating barren-plateau and optimization failures without sacrificing generalization. Empirically TTA achieves top test accuracy ($\approx $100\%) among quantum and classical baselines, is robust to common quantum errors, and realizes aggregate systems with almost 10,000 cumulative layers and 0.2M parameters, implemented as many shallow circuits. Our results are empirical and implementable on near-term platforms, providing a resource-efficient route to scalable multi-class quantum machine learning.

Abstract We present a framework combining Lie group theory and feed-forward neural networks to efficiently generate quantum optimal control pulses for arbitrary unitary operations in superconducting qubit systems, bypassing the need for explicit optimization at inference time. The exponential scaling of the Hilbert space dimension with qubit number makes standard optimization approaches computationally prohibitive when large ensembles of distinct propagators must be processed, a bottleneck that is particularly acute in Trotterized quantum simulation. Our method addresses this limitation by pre-computing a representative set of control pulses via Lie group theory and training neural networks to map target propagators to their corresponding pulses. We demonstrate the approach on superconducting qubit systems of 2, 3, and 4 qubits, finding high reconstruction fidelity for specific combinations of Lie algebra parameters. As a physically motivated benchmark, we apply the methodology to reconstruct control pulses for the Trotter propagators of a neutrino system undergoing collective flavor oscillations. The successful generalization across system types demonstrates that a single model -trained once on hardware-specific random propagators -can serve as a universal control-pulse generator for any target quantum system of compatible Hilbert space dimension, offering a promising route toward scalable quantum simulation.

Abstract Equivariant quantum neural networks are designed to preserve symmetries in quantum machine-learning data, but this property is usually verified only before hardware compilation. We show that a transpiler can preserve the expected unitary symmetry relation while compiling symmetry-related inputs into circuits with different two-qubit gate counts and physical-qubit layouts, so ideal-circuit equivariance does not guarantee symmetry at the level of compiled circuit structure. We formalise this gap with a three-level compliance hierarchy and a taxonomy separating topology-input ansätze, where the symmetry changes the gate topology the compiler sees, from parameter-input ansätze, where it changes only numerical gate parameters and provably leaves controlled-Z counts unchanged under topology-based transpilation. Auditing four published ansatz families, we observe the effect only in the topology-input case. For the Skolik permutation-equivariant weighted-graph ansatz compiled to the IBM Heron Fez simulator target at twelve qubits, sparse graph inputs produce a mean relative controlled-Z asymmetry of 7.3\% across fifty random vertex permutations, with a worst case of 22.5\%. The effect persists across all four Qiskit optimisation levels and is not removed by matched-layout compilation, implicating routing-stage sensitivity to the ordered sparse-edge gate sequence. A density sweep shows that the asymmetry is comparable across intermediate graph densities and vanishes for complete graphs, where the ansatz degenerates into the parameter-input class, and stochastic baselines attribute the realised differences to heuristic routing sensitivity rather than to differing optimal compiled costs. Finally, we propose compile-once-and-relabel, a deployment pattern that removes controlled-Z count asymmetry by construction and reduces compilation cost for orbit-based workflows.

Abstract Entanglement distillation is a fundamental operation in quantum information processing used to obtain higher-fidelity entangled pairs from a supply of less entangled quantum states using local operations aided by classical communication (LOCC). In a physically relevant setting, where states with an initial fidelity of f 0 , probabilistically generated over multiple, m, memory pairs distributed between two parties, Alice and Bob, are pairwise distilled, the optimal policy identifies the system configuration dependent sequence of entanglement generation and distillation operations that need to be performed in order to minimize the expected time to reach some target fidelity f T > f 0 . Here, we formulate and systematically analyze this task as a Markov decision process and using a value iteration algorithm, obtain optimal deterministic policies that minimize the expected waiting time required to achieve a target fidelity. Our results show that the expected waiting time under the optimal policy decreases with increasing generation probability p and number of quantum memories m -as expected. In contrast, it exhibits non-monotonic behavior with respect to f 0 for a fixed fidelity gap, (∆f = f T - f 0 ). While the optimal policy consistently outperforms baseline policies such as the greedy, nested and entanglement pumping policies, its relative advantage is regime-dependent, being determined by the system parameters (p, f 0 , f T , m), and exhibits a nontrivial dependence on the fidelity gap ∆f . Our results highlight the value of formulating entanglement distillation as a Markov decision problem, enabling the systematic design of policies that achieve target fidelity thresholds for quantum information tasks in realistic resource-constrained settings.

Abstract Machine learning (ML) and quantum machine learning (QML) have gained significant importance, as they offer powerful tools for tackling complex computational problems across various domains. An overview of QML's uses in quantitative finance is presented here. The connection between quantum computing and machine learning in financial applications, spanning a range of use cases including portfolio optimization, market prediction and trading, pricing and risk management is examined. The different applications from the literature review are categorized based on specific use cases, ML approaches, optimization methods, and the types of quantum hardware utilized. To facilitate this examination, we employ a morphological box, which allows us to analyze different combinations of these elements across financial use cases.

Abstract We study a family of sparse positive maps on qutrits for which positivity, decomposability, and PPT entanglement can all be analysed explicitly. The block structure of the associated Choi matrices reduces positivity to a Hermitian biquadratic form and leads to exact positivity boundaries for three representative parametric families. For the same families we determine the exact transition between decomposable and non-decomposable maps and construct associated PPT states of two classes. The first consists of witness-adapted deformations naturally tied to the non-decomposability analysis. The second consists of analytically tractable families whose full PPT-entangled branch is detected by fixed positive maps, yielding exact thresholds between separability and bound entanglement. For the trace-preserving subclass, we further compare positivity with a recent eigenvalue bound for 2-positive maps, thereby making the gap between positivity and higher-order positivity fully explicit within this family.

Abstract Calibration summaries are used both to select physical qubits and to parameterize noisy emulators, creating a risk that agreement within a calibration-derived model is mistaken for validation on hardware. We test whether calibration-aware compiler rankings transfer to hardware using weighted-MaxCut instances implemented with the quantum approximate optimization algorithm (QAOA). The evidence comprises four stages: 3,240 historical calibration-derived simulations; a complete 54-pair hardware grid on three IBM Heron r2 processors; exact-circuit repeats 9.3–12.1 days later; and a contemporaneous five-arm refresh experiment. Full-calibration selection improves the median hardware approximation ratio by 0.74 percentage points (pp), with 29 resolved gains and 11 resolved losses. This is a mean-objective effect: its translation to exact-solution probability is instance- and size-dependent, and we do not extrapolate it beyond the tested n ≤ 10 regime. A Qiskit Aer model constructed from the calibration state available before execution reproduced the direction of the measured full-calibration-versus-topology advantage in 35/54 comparisons, but systematically overestimated its size: the simulated advantage exceeded the subsequently measured hardware advantage by a median 1.35 pp. Regressing the measured hardware advantage on the simulated advantage gave a slope of 0.28 (workload-depth case-cluster 95% interval 0.06–0.52), rather than the unit slope of a calibrated predictor. The emulator identified the exact best of six backend-compiler configurations in only 5/18 cases (95% Wilson interval [0.125, 0.509]). By contrast, identical circuits preserved the compiler-effect sign in 16/18 later repeats (r = 0.92). Refreshing the full-calibration mapping yielded a median +0.72 pp gain, whereas the calibration-score difference agreed in sign with the measured refresh benefit in only 9/18 cases. Calibration data are therefore useful for candidate discovery and timely refresh, but their scalar scores are not calibrated predictors of hardware performance or configuration ranking.

Insider Brief A new study analyzes an unpublished Schrödinger manuscript that challenged claims that hidden information could not explain apparently random quantum outcomes. Schrödinger’s model reproduced the expected results of polarization measurements, serving as a mathematical counterexample rather than a complete theory of quantum physics. The manuscript illustrates the complexity of Schrödinger’s views, showing that he could construct a deterministic model while favoring fundamental randomness in nature. Image: Photo by Robert Stump on Unsplash PRESS RELEASE — An unpublished manuscript by Erwin Schrödinger shows how apparently random quantum results could follow definite rules, challenging an argument that such explanations were impossible. The handwritten draft , analyzed in a new historical study posted on arXiv , adds a missing contribution to a wartime dispute over whether quantum mechanics had ended the scientific case for a predictable universe. It also complicates a familiar picture of Schrödinger as a defender of determinism, the idea that events are fixed by preceding conditions. According to physicist Flavio Del Santo, Schrödinger constructed his model to expose a weakness in an argument, rather than to establish how nature actually works. His draft combined a mathematical counterexample with a defense of the possibility that randomness is fundamental. The study presents what Del Santo describes as the first transcription and analysis of the manuscript with a central finding concerning the limits of scientific claims. Schrödinger showed that ruling out one proposed explanation does not necessarily rule out every explanation of the same kind. A Missing Contribution The document survives in the Erwin Schrödinger Archive at the University of Vienna ’s Austrian Central Library for Physics. Titled “Collapse of Determinism,” it consists of three handwritten pages and is undated. Del Santo, affiliated with the University of Geneva and Constructor Univ

Insider Brief Qblox has integrated NVIDIA DGX Spark with its quantum system controller using NVIDIA NVQLink, reporting round-trip latency below 4.0 microseconds on NVIDIA RTX PRO 6000 Blackwell and below 7.2 microseconds on DGX Spark. The integration connects GPU computing with quantum control to support real-time hybrid quantum-classical workloads, including GPU-accelerated calibration and quantum error correction. The system uses NVIDIA CUDA-Q to support development on desktop hardware, with the same code designed to transfer to GPU servers as quantum systems scale. PRESS RELEASE — Qblox , a leader in scalable quantum control architecture, today announced the integration of NVIDIA DGX Spark with a quantum system controller using NVIDIA NVQLink , achieving measured roundtrip latency below 4.0 µs on NVIDIA RTX PRO 6000 Blackwell and below 7.2 µs on NVIDIA DGX Spark. This enables Qblox to support real-time hybrid quantum-classical applications, with a single desktop system that can host quantum, AI, and simulation workloads via NVIDIA CUDA-Q . The same code then carries over to data center graphics processing unit (GPU) servers as systems scale. The integration brings GPU acceleration into the real-time control loop, a key building block for scaling quantum systems to support logical qubits. Qblox ‘s Q1 sequence processors and LINQ deliver the low latency and high throughput the Qblox Cluster needs to work hand in hand with the GPU. GPU-accelerated calibration routines update qubit parameters while experiments run, instead of between them. For quantum error correction, syndrome data reaches GPU-based decoders with low latency, helping identify and correct errors in real time. The milestone builds on the previous work from Qblox with NVIDIA NVQLink announced in October 2025 and on Qblox’s support for the NVIDIA CUDA-Q realtime API in March 2026. It moves the integration from architecture to measured hardware performance, demonstrating Qblox’s a

Insider Brief QCentroid has announced QCentroid Missions, a new QuantumOps capability that helps enterprise teams evaluate computational approaches against business objectives and defined validation criteria. The system uses agents to test classical, quantum-inspired, GPU-simulated and quantum processing unit (QPU) approaches, with recommendations based on benchmarking evidence and the option to retain an existing classical solution. QCentroid Missions uses NVIDIA CUDA-Q for accelerated circuit simulation and is being demonstrated at NVIDIA GTC Berlin from 20–22 October 2026, with rollout to QCentroid Platform customers planned from Q4 2026. PRESS RELEASE — QCentroid today announced QCentroid Missions , a new goal-driven capability in its QuantumOps platform designed to take enterprise teams from a measurable business objective to validated evidence for deciding whether, and how, to evolve an existing computational solution. QCentroid Missions is being demonstrated this week at NVIDIA GTC Berlin. Rather than starting with a quantum algorithm or a predefined technology, a Mission starts with an outcome such as reducing execution time, improving solution quality or reaching a target business metric. Teams define the objective, the computational and operational limits, and the validation gates that must be cleared. Expert agents in QuantumOps then run the experimentation cycle, evaluating potential evolutions of the current solver across classical, quantum-inspired, GPU-simulated and QPU-ready approaches. The resulting recommendation may be classical, hybrid or quantum, including a recommendation to retain the current classical solution when the evidence supports it. “Quantum teams are small, while the number of questions coming from the business continues to grow,” said Carlos Kuchkovsky, CEO and co-founder of QCentroid . “With Missions, teams no longer have to manually drive every stage of an experiment. They define what they want to improve, how far the system

Insider Brief Black Kite has introduced Quantum Readiness controls within its Cyber Rating platform to assess observable signs of post-quantum cryptography readiness across an organization’s third-party vendors. The new controls examine indicators such as hybrid post-quantum key exchange, certificate signature readiness and assets without an identified migration path, integrating the results into the platform’s SSL/TLS Strength category. The feature is designed to help organizations track vendor readiness, identify potential gaps in supply-chain cryptographic security and prepare for post-quantum migration requirements. PRESS RELEASE — Black Kite , the leader in third-party cyber risk management, today announced the release of Quantum Readiness, a new set of controls within the SSL/TLS Strength category of the Black Kite Cyber Rating that evaluates quantum agility across an organization’s third-party vendor ecosystem. Quantum Readiness surfaces which vendors are quantum-ready or adopting quantum-safe encryption methods, providing an early indication of security maturity and preparedness for the post-quantum era. Quantum computers capable of breaking today’s encryption do not exist yet, but experts predict “Q-Day” could arrive as early as 2028. The risk is also retroactive: in “harvest now, decrypt later” attacks, bad actors are already collecting encrypted data to decrypt once quantum computers are powerful enough. Organizations need to prepare now – for many, the shift to quantum-safe encryption is underway, making quantum agility a key indicator of vendor security maturity and readiness. “Third-party cyber risk management needs to account for where risk is going, not only where it exists today,” said Ferhat Dikbiyik, Chief Research & Intelligence Officer (CRIO), Black Kite. “We built Quantum Readiness to give customers early visibility into quantum agility across their supply chains and help them understand

Insider Brief Florida’s first statewide quantum-safe network segment is operational, connecting Palm Beach State College and Florida Atlantic University in Boca Raton using IonQ quantum key distribution technology. Supported by a $1 million FloridaCommerce grant, the connection went live Oct. 15 over Palm Beach County’s dark fiber infrastructure to strengthen data security between the institutions. Connections to Miami Dade College and FAU’s Jupiter campus are planned within three months, with further statewide expansion dependent on funding. PRESS RELEASE — Palm Beach State College (PBSC) President Ava L. Parker , JD announced Wednesday night that the first segment of Florida’s statewide quantum-safe network is operational. The system links PBSC to Florida Atlantic University in Boca Raton over Palm Beach County’s dark fiber infrastructure. Supported by a $1 million defense infrastructure grant from FloridaCommerce, Palm Beach State College is leading the development of the network’s first segment in partnership with Florida LambdaRail, Florida Atlantic University, Palm Beach County and IonQ. The segment uses IonQ quantum key distribution technology to strengthen the security of data transmitted between the participating institutions and establishes a foundation for expanding quantum-secure communication across Florida. Parker made the announcement at the college’s Historic Building in West Palm Beach, the future home of PBSC’s Quantum Innovation Center, the evening before Quantum Beach 2026 . The link went live Oct. 15, 2026. “”This partnership is a model for how higher education, industry and government can work together to build the infrastructure and talent that will drive Florida’s future,” said Parker. “By connecting students to leading-edge technologies while strengthening secure communications across our region and state, we are creating opportunities that extend far beyond our campuses. At the same time, we are pre

Researchers at Fraunhofer IAF have developed a laser-enhanced quantum sensor that combines high magnetic-field sensitivity with a large dynamic range. Using laser threshold magnetometry, they improved the ratio of sensitivity and dynamic range by a factor of up to 590 compared with state-of-the-art approaches. The breakthrough is enabled by the first demonstration of 100% optical contrast, combined with strong laser readout signals. The results, published in Nature Communications, open up new prospects for medical diagnostics, navigation, and resource exploration.

Insider Brief ZuriQ and Rhonexum have signed a multi-year commercial agreement under which Rhonexum will supply cryogenic integrated-circuit technologies and customization services for ZuriQ ‘s trapped-ion quantum computing roadmap. The agreement includes an initial product delivery scheduled for the end of 2026, future product orders and deployments, and technical cooperation that gives ZuriQ access to selected Rhonexum technologies and product developments. The companies aim to address quantum processor scaling challenges, including control-signal overhead per qubit, by combining ZuriQ ‘s trapped-ion architecture with Rhonexum ‘s cryogenic electronics expertise. PRESS RELEASE — ZuriQ and Rhonexum have announced a multi-year commercial framework agreement. Under the agreement, Rhonexum will supply cryogenic integrated-circuit technologies and customisation services to ZuriQ, which will evaluate the potential of each of these solutions to advance its trapped-ion quantum computing roadmap. This partnership brings together ZuriQ ’s trapped-ion quantum computing expertise and Rhonexum ’s cryogenic electronics technologies to address future scaling and performance requirements. It establishes a framework for future orders, product deployments, and technical collaboration. Quantum computing is rapidly accelerating toward industrial deployment and scalable commercial systems. As quantum processors scale, demand is growing for specialised hardware and electronics that improve performance, reduce complexity, and enable more compact system architectures. A longstanding challenge in scaling trapped-ion quantum computing is to reduce the overhead in control signals per qubit that travel from room-temperature sources into a cryogenic environment. ZuriQ ’s architectural advances, together with Rhonexum ’s cryogenic electronics expertise, provide a unique approach that can enable denser qubit arrays while retaining flexible reconfiguration capabilities. Th

Insider Brief The UK and Singapore held their 11th Financial Dialogue in Singapore, discussing cooperation in digital finance, AI, quantum technologies, capital markets and sustainable finance. On quantum technologies, both countries reviewed quantum security approaches, guidance for financial institutions transitioning to post-quantum cryptography, and lessons from Singapore’s Quantum Key Distribution sandbox with industry partners. The two countries also discussed financial market innovation and regulatory cooperation ahead of the UK’s G20 Presidency and Singapore’s ASEAN Chairmanship in 2027. PRESS RELEASE — The United Kingdom (UK) and Singapore held the 11th UK-Singapore Financial Dialogue in Singapore today. Reaffirming their strong and longstanding partnership, the discussions focused on advancing cooperation in digital finance and innovation, capital markets, sustainable finance, and regional and multilateral initiatives. Digital Finance and Innovation The UK and Singapore exchanged views on digital finance and innovation, including taking stock of and advancing their cooperation in digital assets, artificial intelligence (AI), and quantum technologies.  Discussions on digital assets and financial market infrastructure covered initiatives from both jurisdictions aimed at supporting cross-border use cases for tokenisation and wholesale digital markets. These included the Monetary Authority of Singapore (MAS)’s Project Guardian [footnote 1] and BLOOM, [footnote 2] Global Layer One (GL1), [footnote 3] alongside the UK’s Wholesale Financial Markets Digital Strategy, [footnote 4] the work of the UK Wholesale Digital Markets Champion, [footnote 5] the Digital Securities Sandbox, [footnote 6] and ongoing work of the Bank of England (BoE) and the Financial Conduct Authority (FCA) on tokenisation and wholesale digital markets. Developments in crypto-assets and stablecoins and the implications of digital money for wholesale markets and inst

Ever since quantum mechanics first described particles, like electrons, as rippling waves, researchers have wondered if those waves could be trapped in place. Writing today in Science a century later, a team of Columbia University researchers reports waves of electrons becoming trapped for the first time in a metal called Pd₅AlI₂.

Insider Brief Sparrow Quantum has appointed founder Peter Lodahl as CEO, succeeding Kurt Stokbro, who will remain involved as an executive advisor and board member. The company plans to focus on integrating, controlling and connecting its photonic quantum chip technology into larger computing systems designed for fault-tolerant quantum computing. Sparrow has strengthened its leadership team with new commercial and financial appointments and established a Scientific Advisory Board to guide its technical roadmap. PRESS RELEASE — Sparrow Quantum today announced that its founder and former Chief Quantum Officer, Professor Peter Lodahl, has been appointed Chief Executive Officer as part of a planned leadership transition. He succeeds Kurt Stokbro, an early investor who led the company’s development into a growing commercial quantum technology scale-up. Kurt will remain closely involved as Executive Advisor and member of the board. The appointment completes a strengthening of Sparrow Quantum ’s leadership team that began in May, when former Danish Tech Ambassador Anne-Marie Engtoft Meldgaard joined as Chief Commercial Officer. The company has also established a new Scientific Advisory Board to provide external guidance on its technical roadmap. Having developed and delivered its quantum photonic chip technology, Sparrow Quantum will now focus on the integration, control, and connection of reliable quantum light within larger computing systems. Peter Lodahl is uniquely positioned to lead that work. As a world-leading expert in photonic quantum technology, his research has been instrumental in establishing Sparrow’s position in photonic quantum hardware. Since the company spun out of the Niels Bohr Institute at the University of Copenhagen, it has built world-leading capabilities, an ambitious team, and growing engagement from customers and partners. “Kurt has been instrumental in turning Sparrow ’s scientific foundations into a growing technology company. He he

Insider Brief SEEQC reported simulation results showing that combining its chip-based pre-decoder with NVIDIA Ising reduced quantum error-correction decoding time and logical error rates by approximately 50% compared with using Ising alone. The architecture places specialized processing closer to the quantum processor to reduce data transfers and support faster communication with GPU-based computing systems. SEEQC plans to integrate the demonstrated components into a quantum processor connected to high-performance computing infrastructure and evaluate further improvements in error correction and scalability. PRESS RELEASE — –   SEEQC , Inc. (“SEEQC” or the “Company”),a chip-based quantum computing company, today announced results demonstrating significant performance improvements in quantum error correction decoding through a digital interface optimized multi-stage decoding architecture combining SEEQC’s chip-based pre-decoder technology with the NVIDIA Ising open family of AI models . SEEQC’s chip-based pre-decoder was integrated in a simulated quantum processor and architecture stack incorporating realistic decoder latency at scale, as a backend to NVIDIA Ising Decoding with SEEQC Digital Link and NVIDIA NVQLink providing the framework for low-latency communication between quantum and GPU-accelerated compute environments. Compared with operating NVIDIA Ising as a standalone pre-decoder, the combined multi-stage pre-decoder architecture demonstrated an approximately 50% reduction in decoding latency and logical error rate performance, the two key metrics that dictate the scalability of a fault tolerant quantum system. The overheads associated with error correction are enormous and can increase exponentially as systems scale towards useful computation. Therefore, a 50% improvement in these key scaling bottleneck metrics have a significant impact on the overall scalability and efficiency of a quantum processor. The results demonstrate how specialized proce

Insider Brief Ericsson Canada and École de technologie supérieure (ÉTS) have launched a Mitacs-supported research project to develop quantum computing methods for improving telecom network operations. The research team will investigate variational quantum algorithms, focusing on error mitigation and optimization through experiments using quantum hardware and simulations. The project is the second Mitacs-funded academic collaboration under Ericsson Canada’s Montreal Quantum Research Hub, which supports quantum research and talent development in Quebec. PRESS RELEASE — Ericsson Canada and École de technologie supérieure (ÉTS) have teamed up to further quantum computing research in Quebec, one of the country’s primary quantum computing centres. With support from the Mitacs Accelerate program, the project aims to develop better quantum computing methods that will help run and manage telecom networks more efficiently, while also training students and researchers in cutting-edge quantum technology that supports Canada’s leadership in this field. “Quantum computing will unlock new ways to make telecommunications networks more efficient, and Canada is well positioned to lead that work,” says Nishant Grover, President, Ericsson Canada. “Through our Montreal Quantum Research Hub and our partnership with ÉTS, supported by Mitacs Accelerate, we’re bringing together world-class research and industry expertise to advance practical quantum methods for telecom network operations.” The Honourable Mélanie Joly, Minister of Industry and Minister responsible for Canada Economic Development for Quebec Regions, says: “Quantum technologies will shape the course of our future and Canada is a world leader in this emerging technology space. As a long-trusted partner in Canada’s technology ecosystem for more than 70 years, we were encouraged by the establishment of Ericsson Canada’s Quantum hub in Montreal, and we welcome this new partnership which will further strengthen Canada’s

Insider Brief Symmatrics has appointed Andrew Hallman, a former senior CIA and ODNI official who now works at Leidos, to its Strategic Advisory Board. Hallman brings more than 30 years of intelligence and security experience, including serving as Deputy Director of the CIA for Digital Innovation and performing the duties of Principal Deputy Director of National Intelligence. Symmatrics is developing cybersecurity products based on One-Time Pad Symmetric Key (OTPSK) encryption, which the company says are designed to protect data and communications against AI-driven and quantum-related threats. PRESS RELEASE — Symmatrics , the cybersecurity company pioneering one-time pad encryption at internet scale and building the new trust layer for the AI and post-quantum era, today announced the appointment of Andrew Hallman to its Strategic Advisory Board. Hallman joins the company as organizations across government, defense, and critical infrastructure sectors face escalating cybersecurity risks driven by artificial intelligence and the emergence of quantum computing. A respected national security leader, Hallman  brings more than three decades of intelligence and security experience, including senior leadership roles at both the Central Intelligence Agency (CIA) and the Office of the Director of National Intelligence (ODNI).  He is currently Vice President and Strategic Account Executive for the Intelligence Community at Leidos, Inc. “Andrew’s experience leading the nation’s most critical intelligence and security initiatives makes him a valuable addition to our advisory board,” said Walter Raquet, Chairman and CEO of Symmatrics . “As AI accelerates cyber threats and quantum computing challenges traditional encryption, Andrew’s perspective will help guide our efforts to develop technologies protecting governments, enterprises, and critical infrastructure from the next generation of cyber risks.” From 2019-2020, Hallman

Join us online on October 22 as Quantum Beach 2026 brings researchers, entrepreneurs, investors and industry leaders to the Palm Beach County Convention Center in West Palm Beach, Florida. Explore the ideas, investments and partnerships shaping the quantum economy, from advances in quantum computing to the practical work of building businesses, preparing a skilled workforce and developing the infrastructure needed to support growth. With a focus on Florida and connections across the wider quantum community, Quantum Beach examines what it takes to move quantum technology from research toward commercial use. Watch the livestream below to follow the conversation and hear perspectives on the opportunities and challenges ahead.

Insider Brief RhymeQ raised $2.2 million in pre-seed funding to develop software designed to let Python developers program quantum computers. Its Rhyme compiler translates conventional code for multiple quantum processors and NVIDIA CUDA-Q, supporting both quantum simulators and hardware. The funding will support engineering hires, enterprise platform development, hardware partnerships and expansion of its developer community. RhymeQ, a startup making quantum computers accessible to software developers across the world, has raised a $2.2 million pre-seed round led by Ground State Ventures , with participation from Vanagon Ventures, Plug and Play , and Freiraum Ventures. Quantum computers promise to solve significant problems and expand the reach of supercomputing and AI, for instance in chemicals, pharmaceuticals, finance, or manufacturing. However, coding for a quantum computer currently requires a PhD in quantum physics. Relatively few people globally are currently capable of that.  RhymeQ has developed Rhyme, a new abstraction layer that allows every developer with basic Python skills to code for quantum. The actual coding is familiar and conventional, while the company’s compilers handle the translation for quantum computers. What’s more, it’s compatible across multiple quantum processors, with no hardware lock-in. “We are on a mission to make quantum computers programmable by every developer on the planet,” says RhymeQ founder and CEO Daniel Volz. “While vibe coding is taking over the classical programming world, the situation is not so simple in the quantum world. Quantum circuits can only be debugged by PhD-level physicists. With Rhyme, any programmer can both develop and debug production-ready code to run on quantum computers at enterprise level.” Volz previously led quantum computing initiatives for McKinsey and BASF and co-founded quantum startup Kipu Quantum. He co-founded RhymeQ in 2026 with CTO Tamás Varga and COO Christina Wu. Varga, the inventor

Unlike classical physics, quantum mechanics generally cannot tell us exactly what will happen in an individual event. Instead, it predicts the probabilities of different outcomes. As one of the theory's early pioneers, Erwin Schrödinger played a key role in debates about what this randomness really means. However, part of his contribution has stayed hidden for more than 80 years.

Determining the steady state of an open quantum system is crucial for characterizing quantum devices and studying various physical phenomena. Often, computing a single steady state is insufficient, and it is necessary to explore its dependence on multiple external parameters. In such cases, calculating the steady state independently for each combination of parameters quickly becomes intractable. Perturbation theory (PT) can mitigate this challenge by expanding steady states around reference parameters, minimizing redundant computations across neighboring parameter values. However, PT has two significant limitations: it relies on the pseudo-inverse – a numerically costly operation – and has a limited radius of convergence. In this work, we remove both of these roadblocks. First, we introduce a variational perturbation theory (VPT) and its multipoint generalization that significantly extends the radius of convergence even in the presence of non-analytic effects such as dissipative phase transitions. Then, we develop two numerical strategies that eliminate the need to compute pseudo-inverses. The first relies on a single LU decomposition to efficiently construct the steady state within the convergence region, while the second reformulates VPT as a Krylov space recycling problem and uses preconditioned iterative methods. We benchmark these approaches across various models, demonstrating their broad applicability and significant improvements over standard PT.

We present a symmetry-enabled direct quantum protocol for computing many-body Green's functions, a central tool for studying strongly correlated quantum systems. Our protocol relies only on native time evolution and straightforward measurements available on current hardware platforms. By exploiting parity symmetry—satisfied by a broad class of Hamiltonians in condensed matter physics and quantum chemistry, including the Fermi–Hubbard and Heisenberg models—we introduce a tailored quench spectroscopy scheme that recovers both the real and imaginary parts of two-point time correlators, from which Green's functions can be reconstructed via efficient classical signal processing. We further develop a tailored symmetric quantum Gibbs sampler that prepares parity-resolved (symmetric and antisymmetric) thermal states, enabling finite-temperature extensions within the same framework. Finally, we show that the same symmetry-based measurement primitive extends naturally to out-of-time-ordered correlators (OTOCs). Our results provide a practical route to estimating symmetry-resolved dynamical correlators on near-term and early fault-tolerant quantum hardware.

Mean-field Hartree theory is a central tool for reducing many-body dynamics to an effective one-particle evolution. This approximation has been employed when the Hamiltonian governing the many-body dynamics is not Hermitian. Indeed, non-Hermitian Hamiltonians model particle gain/loss or the evolution of open quantum systems between consecutive quantum jumps. Furthermore, the validity of the Hartree approximation for generic non-Hermitian Hamiltonians lies at the basis of a quantum algorithm for nonlinear differential equations. In this work, we show that this approximation can fail.First, we consider the most general bosonic mean-field Hamiltonian with two-body interactions and we prove that, for non-Hermitian Hamiltonian, the Hartree equation does not capture the correct second time derivative of the one-particle marginal state at t = 0 in the thermodynamic limit. Then, we analytically solve a model of N bosonic qubits with a purely anti-Hermitian Hamiltonian, compute the limit for N → ∞ of the one-particle marginal state and show that it does not agree with the solution of the non-Hermitian Hartree equation. We further show that there exists an initial condition such that the exact one-particle marginal state undergoes a finite-time transition to a mixed state, a phenomenon that is completely absent in the case of Hermitian Hamiltonians. Finally, we simulate a non-Hermitian Hamiltonian with real spectrum and show that, also in this case, there are initial conditions for which the Hartree equation does not reproduce the correct one-particle marginal state in the limit N → ∞ .Our findings challenge the validity of the mean-field Hartree approximation for non-Hermitian Hamiltonians, and call for additional conditions for the validity of the mean-field regime to model the dynamics of particle gain and loss and the open-system dynamics in bosonic many-body systems.

In this work, we examine the consequences of the existence of a finite group of matrix product unitary (MPU) symmetries for matrix product states (MPS). We generalize the well-understood picture of onsite unitary symmetries, which give rise to virtual symmetry defects given by insertions of operators in the bonds of the MPS. In the MPU case, we can define analogous defect tensors, this time sitting on lattice sites, that can be created, moved, and fused by local unitary operators. We leverage this formalism to study the gauging of MPU symmetries. We introduce a condition, block independence, under which we can gauge the symmetries by promoting the symmetry defects to gauge degrees of freedom, yielding an MPS of the same bond dimension that supports a local version of the symmetry given by commuting gauge constraints. Whenever block independence does not hold (which happens, in particular, whenever the symmetry representation is anomalous), a modification of our method which we call state-level gauging still gives rise to a locally symmetric MPS by promotion of the symmetry defects, at the expense of producing gauge constraints that do not commute on different sites.

We construct an important missing piece in the entanglement theory of pure three-qubit states, which is a polynomial measure of W-entanglement. This works in parallel to the three-tangle, which is a polynomial measure of GHZ-entanglement, and to the bipartite concurrence, which is a polynomial measure of bipartite entanglement. We also show that these entanglement measures are ordered, the bipartite measure is larger than the W measure, which is larger than the GHZ measure. It is meaningful then to consider these three types of three-qubit entanglement, which are also ordered, bipartite is weaker than W, which is weaker than GHZ, in parallel to the order of the three kinds of equivalence classes of entangled three-qubit states.

We show that, for sudden quenches, the work distribution reduces to the statistics of the traces of powers of Haar unitaries, which are random unitary matrices drawn uniformly from the unitary group. For translation-invariant quadratic fermionic chains with interactions extending to m neighbors and periodic boundary conditions, the Loschmidt amplitude admits a unitary matrix model / Toeplitz representation, which yields a work variable of the form W = ∑ r ≤ m a r ℜ Tr ⁡ U r (and in models with pairing terms -superconducting pairing- additional b r ℑ Tr ⁡ U r terms appear). By invoking multivariate central limit theorems for vectors of traces of unitaries, we obtain a Gaussian distribution for P ( W ) with variance V a r ( W ) = 1 2 ∑ r r ( a r 2 + b r 2 ) and asymptotic independence across different powers. We also characterise the conditions under which non-Gaussian tails arise, for example from many interaction terms or their slow decay, as well as the appearance of Fisher-Hartwig singularities. We illustrate these mechanisms in the XY chain. Various numerical diagnostics support the analytical results.

Abstract Quantum batteries are quantum systems that store energy and deliver it on demand, and their practical value hinges on how fast they can be charged. While collective charging protocols and global control are known to enhance charging power, it remains unclear how the battery’s internal interaction architecture itself constrains performance. Here we study interacting fermionic batteries whose internal couplings are encoded by a graph adjacency matrix and which are charged through a uniform interaction with an external fermionic device. We prove that the star topology uniquely maximizes the initial slope of the charging power at zero local field. At finite field, we derive an exact spectral criterion for outperforming the star and construct a star-like family that satisfies it. Based on numerically established correlation, we expect these findings to extend to the maximal average charging power as well. To confirm the dominance of the star architecture, we complement the analysis by an exhaustive sweep over all connected graphs with N ≤ 7 vertices, and by larger
random-graph benchmarks.

We examine the conditions under which quantum parameter estimation is compatible with the concept of a ``true'' quantity value: a unique value of the estimated quantity that exists prior to and independently of measurement. While quantum parameter estimation typically assumes that the quantity to be estimated is a parameter, we argue that this assumption can be lifted, opening the way to a more general formulation of estimation that may apply even in situations where the quantity to be estimated is no longer a parameter, but instead a quantum variable susceptible to quantum fluctuations. We identify three assumptions that characterize the way estimation is often presented in the quantum metrology literature, namely, as a procedure for inferring an unknown ``true value", which is assumed to be unique and to exist prior to and independently of measurement. Using our more general framework, we prove a no-go theorem showing that the preceding assumptions are jointly incompatible with two further assumptions: the completeness of the quantum state (no `hidden variables'), and the presence of entanglement between the probe systems and the system under measurement. We note that the presence of such entanglement is a generic prediction of standard quantum theory. Consequently, if one is not willing to accept hidden variables, nor willing to modify standard quantum theory by introducing a new physical mechanism that destroys entanglement at some scale or regime, then a realist account of estimation is ultimately impossible.

We develop an end-to-end framework for assessing a quantum-computing application in industrial materials science: the screening of strongly correlated oxygen-electrode materials for SOFCs and SOECs. We formulate the materials problem in terms of interface observables including oxygen-vacancy formation energies, vacancy migration barriers, and electronic conductivity. We describe how these observables can be obtained using a diagrammatic GW-based embedding, either GW+DMFT or self-energy embedding theory (SEET), applied to a DFT-screened shortlist. The atomistic electrode/electrolyte interface defines the electronic structure problem from which the correlated impurity models are constructed. Quantum impurity solvers would provide the finite-temperature impurity Green's functions required by the embedding. The computational challenges that classical solvers may encounter as the interacting active space grows, together with the polynomial scaling of quantum Hamiltonian simulation for efficiently represented discretized models, open an opportunity for quantum advantage. We identify the benchmarks needed to assess this opportunity through convergence of vacancy and migration energetics and comparison with the best applicable classical solvers. We provide illustrative logical qubit counts and identify the thermal state preparation, simulation, measurement, and repeated-solve costs needed for a complete resource assessment. We connect microscopic observables to macroscopic engineering metrics using a continuum model for mixed ionic--electronic conducting oxygen electrodes that couples oxygen surface exchange, solid-state oxygen transport, electrode microstructure, and finite electrode thickness. Finally, we estimate the potential worldwide business value of improved electrode materials under SOFC and SOEC deployment scenarios informed by public technical targets and electrolyser deployment data.

Pure-state deep thermalization predicts that, after sufficient scrambling, projected ensembles approach universal distributions that contain information beyond the reduced density matrix. In realistic quantum systems, however, noise is unavoidable and the projected states are generally mixed. Whether mixed-state deep thermalization admits an analogous universal limiting distribution has remained unclear. Here we answer this question for quantum dynamics containing local quantum channels, i.e., errors. We show that the late-time mixed-state projected ensemble is completely determined by the normalized Choi state of the error channel and is universal, independent of the microscopic details of the underlying unitary dynamics. We establish this result analytically for dual-unitary circuits, global Haar-random dynamics, and local Haar-random circuits at large local dimension, and verify it numerically in qubit circuits and kicked Ising dynamics. In a solvable setting, we further find exponentially fast convergence to the limiting ensemble. Our results extend deep thermalization to noisy quantum dynamics and establish a direct correspondence between quantum errors and universal random mixed-state ensembles.

We propose a new method for proving $L^2$ and modified logarithmic Sobolev inequalities with constants independent of system size for quantum Gibbs samplers whose Lindblad generators satisfy Kubo-Martin-Schwinger (KMS) detailed balance. We first establish the $L^2$ logarithmic Sobolev inequality by transporting it along a temperature-dependent path from the infinite-temperature product state to the target Gibbs state while maintaining a size-independent decay rate for the sandwiched Rényi-2 divergence. A tensor-power argument, combined with the quantum asymptotic equipartition property, then transfers this decay bound to relative entropy, yielding the modified logarithmic Sobolev inequality. This approach provides a general framework for proving size-independent logarithmic Sobolev inequalities for quantum Gibbs samplers. We apply it to two regimes: one-dimensional quantum spin chains at every finite temperature, and finite-range quantum spin systems at sufficiently high temperature in any fixed dimension.

Tensor-network simulation of quantum circuits depends on contraction orders with low computational cost and small intermediate tensors, found without excessive planning time. We present ArcTN, a contraction-order optimization framework with two search presets. Light keeps planning overhead low, and Heavy spends more effort on refinement. Both combine randomized-greedy construction, subtree reconfiguration, and parallel tempering with stage-specific stopping rules. ArcTN also provides Fixed and Dynamic slicing to meet tensor-size limits and executes the returned orders. On the 30 QC32 quantum-circuit networks completed by all eight compared configurations, Light reduces FLOPs by 61.32% and plans 1.62$\times$ faster than Cotengra Auto/CMA-ES, and Heavy reduces FLOPs by 43.83% and plans 7.21$\times$ faster than Cotengra AutoHQ/Optuna. Heavy also needs 11.85% fewer FLOPs than OMECO TreeSA-8 and plans 1.33$\times$ faster. Dynamic slicing meets the size limits in all 90 runs on 18 scalar-output networks and reduces total sliced FLOPs by 31.99% relative to Fixed slicing, at the cost of longer planning. With a common NumPy executor, Heavy has the lowest combined planning and execution time among five configurations on the runs that all of them completed. On 672 networks built from 320 MQT Bench circuits, Heavy obtains the lowest geometric-mean FLOPs on the 142 large networks while planning 3.1$\times$ and 31$\times$ faster than Cotengra AutoHQ and Hyper128.

Randomised quantum simulation algorithms such as qDRIFT reduce circuit depth by replacing deterministic product formulas with stochastic compilations, but achieving high accuracy can require many steps. In vanilla qDRIFT, Hamiltonian terms are sampled with probabilities proportional to their coefficient magnitudes. We propose StateDRIFT, a variant of qDRIFT which optimises its sampling distribution to estimate time-evolved quantities using knowledge of the initial state and target observable, with a provable truncation bound that keeps qDRIFT's guarantees. The distribution at each depth is chosen by solving an optimisation problem targeting bias and/or variance. StateDRIFT can significantly reduce the bias and variance of estimators, and hence circuit depth, which we test on short-time dynamics of lattice models and molecules under Jordan-Wigner up to 18 qubits. For example, with BeH2 StateDRIFT can reduce the number of two-qubit gates required to achieve a given accuracy from 11,201 to 983. StateDRIFT involves measuring observables and commutators on the initial state, so we propose two practical ways to estimate these: classical surrogates such as tensor networks, and classical shadows, which recover most or all of the saving from exact oracles in the systems tested.

Metallo-DNA nanowires serve as a versatile, programmable scaffold for molecular-scale electronics. In this work, we demonstrate that periodic heavy-metal coordination fundamentally reshapes the electronic landscape of DNA, generating dispersive, metal-centered conduction bands rather than isolated localized states. Driven by enhanced inter-layer coupling, where second nearest-neighbor hopping plays a crucial role: the conduction bandwidth can approach 1 eV, more than double that of canonical DNA. These broad bands suggest enhanced robustness of transport against structural fluctuations. As a result of relativistic effects, in these quasi-one-dimensional materials, spin-orbit (SO) coupling enhances band dispersion and governs spin-dependent transport. We predict that although ligand hybridization reduces atomic SO splitting, the effective SO splitting in these nanowires is comparable to the next-nearest-neighbor hopping strength, which results in considerable spin mixing. We find that Hg2+-coordinated nanowire exhibit pronounced spin-flip conductance comparable to spin-conserving conductance across the LUMO manifold. This efficient spin conversion remains robust over extended molecular lengths and is accompanied by a set of highly delocalized unoccupied states with oscillating nodal structures, readily accessible under low-bias transport measurements. In contrast, the Ag+-coordinated nanowires exhibit weak spin-flip scattering that is more than an order of magnitude smaller than spin-preserving transport. This duality establishes the choice of coordination metal as a decisive parameter to govern metal-metal interaction, electron delocalization, and spin-dependent transport. Overall, our findings demonstrate how relativistic effects and quantum confinement intersect in these bio-templated, quasi-one-dimensional molecular conductors.

How much entanglement can two distant laboratories share when their connection is noisy? We relate this question to deciding which of two quantum hypotheses is present. Our one-shot bounds apply to entanglement generation over a quantum channel and to one-way entanglement distillation from a shared state. We use Cheng's trace inequality to bound the infidelity of a Petz decoder in terms of a binary hypothesis testing cost. Applying the inequality before averaging over codes reduces the error analysis to computing a second moment of random subspaces. The proof covers every integer target dimension and treats rank-deficient states explicitly. A corollary expresses the achievable entanglement through hypothesis-testing coherent information, with a single logarithmic error slack and exact integer rounding. We also prove an error-preserving conversion from entanglement generation codes to entanglement transmission codes: the target dimension decreases by only a constant factor at fixed error, and the decoder is the original decoder followed by local processing. Consequently, for both entanglement generation and entanglement transmission, arbitrary pure reference-input states yield the same coherent-information rate, second-order Gaussian correction at the original error tolerance, and explicit achievable logarithmic remainder. For commuting testing hypotheses, the logarithmic remainder improves to a constant. These results give a direct route from binary distinguishability to explicit recovery guarantees and finite-resource quantum communication rates.

Randomized benchmarking (RB) returns a single decay parameter or gate error rate, but when the noise is gate-dependent that parameter is notoriously difficult to interpret. We study RB and related random-circuit benchmarks under small gate-local Markovian noise by factorizing each noisy gate into its ideal action followed by the exponential of a small error generator and then perturbing the RB $\mathscr{L}$ matrix, which models the RB decay. For any low-error gate set that satisfies the requirements of RB (it is a sequence-asymptotic unitary 2-design), we show that Pauli-stochastic error rates contribute linearly to the RB decay parameter, while Hamiltonian error rates contribute through a gauge-invariant quadratic form. Pauli-correlation and active generators are absent from the linear term and enter only at higher order. For the single-qubit native gate set $\{X_{π/2},Y_{π/2}\}$ we derive this quadratic form explicitly in terms of three first-order gauge-invariant (FOGI) coordinates: the two intrinsic over-rotations and one relational axis-tilt error. The resulting formula explains the dependence of DRB on the sampling distribution and the compilation dependence of CRB. These results turn RB decay rates into interpretable functions of experimentally meaningful elementary error rates.

Mechanically compliant mirrors are key components in cavity optomechanics. However, the requirements to achieve the best optical and mechanical performance are usually in direct competition. A high reflectivity for tightly focused beams entails thick reflectors, whereas ultracoherent flexural nanomechanics necessitates thin membranes. We eliminate this trade-off by introducing high-refractive-index nanopillar metasurfaces on top of a thin membrane. We pattern a 50 micrometer-diameter array of nanopillars to form a photonic crystal. The flat band behavior of guided resonances in the photonic crystal enables a reflectivity of 99.82(1)% for a tightly focused beam of 7 micrometer waist. The combination of two guided resonances creates a 100 nanometer-wide high-reflectivity band around 1550 nanometer. Simultaneously, the nanopillar patterning realizes a density-modulated phononic crystal that isolates an ultracoherent localized mechanical mode with a $Q\cdot f$-product of $2\cdot 10^{14}$Hz. The demonstrated nanopillar metasurfaces enable lightweight mirrors for room-temperature quantum optomechanics and for use as levitated mirrors or lightsails.

Quantum error-correcting code (QECC) implementations are hybrid software-control systems: measured syndromes drive decoder dispatch, recovery actions, and logical checks. Existing QECC verification techniques can prove formal obligations, and general quantum testing can expose final failures, but developers still lack a scalable testing workflow that generates concrete faults and explains where a QECC repair path first diverges. This paper presents ConQEC, to our knowledge the first concolic testing framework for QECC implementations. By combining concrete (Pauli) fault replay with symbolic repair-path constraints, ConQEC generates tests that expose not only final logical failures but also fault--syndrome--decoder--recovery (FSDR) diagnostics: the injected fault, observed syndrome, decoder decision, recovery action, oracle result, and earliest divergent stage. Its symbolic encoding of Pauli faults, syndrome predicates, decoder and recovery relations, and oracle checks enables this diagnostic workflow to scale beyond exponentially increasing amplitude-level quantum-state reasoning. We implemented ConQEC and evaluated it on generated source-level QECC families and public QECC artifacts with up to thousands of qubits. ConQEC detects the seeded bug in every experimental case and reports a replay-valid, fault-localizing FSDR witness for each.

We construct a quantum theory of light in nonlinearly responding materials with dispersion and absorption and, in particular, show the emergence of non-Gaussian noise associated with nonlinear absorption processes. Our theory is based on a path-integral formulation of the microscopic Huttner-Barnett model including cubic matter self-interaction required for $χ^{(2)}$ nonlinear processes. We show that the noise polarization emerges naturally from a decoupling of the stochastic weights of the bath response which, in case of cubic self-interactions, leads to a decoupling via Airy functions. As the theory is, by construction, consistent with the nonlinear fluctuation-dissipation theorem, it constitutes a viable quantum theory of light in nonlinear media.

Narrow-linewidth lasers are essential for various key atom-laser interaction processes and optical setups in quantum coherent control, quantum precision measurement, and quantum information science. The Pound-Drever-Hall (PDH) technique is the standard method for the frequency-stabilization of narrow-linewidth lasers, but the inherent time delay in its feedback loop inevitably induces excessive phase noise, commonly known as servo bumps. Previous solutions primarily rely on additional optical components outside the electronic feedback control loop. Here, we propose and implement a generic method based on the Smith predictor to address the time-delay issue entirely within the electronic part of the PDH feedback control loop. We systematically demonstrate its capability to suppress phase noise and reduce servo bumps by adding only a single Field-Programmable Gate Array (FPGA) controller to the loop. This class of methods is demonstrated to be conceptually concise with minimal hardware overhead, effective in practice, and holds potential for a wide variety of future applications.

We investigate the behaviour of Krylov complexity as the number of degrees of freedom of a quantum system increases. Specifically, we show that for tensor products of commuting subsystems, the leading excess complexity is controlled by a weighted variance of the subsystem Lanczos coefficients. This provides a quantitative measure of dynamical heterogeneity and a precise characterization of synchronous evolution. We also show that Krylov entropy is able to disambiguate the information associated with subsystems composition from that generated by dynamical mismatch, and that the same Lanczos variance controls the leading mismatch contribution to both complexity and the entropy. Our results establish excess complexity and Krylov entropy as complementary probes of the emergence of collective dynamics in large quantum systems.

Amplitude encoding stores an N-degree-of-freedom structural mode using ceiling(log2 N) qubits. This article develops an evaluation framework for variational quantum eigensolvers in finite-element structural dynamics. A Cholesky transformation maps the generalized eigenproblem to a symmetric mass-orthonormal Hamiltonian, ensuring Euclidean quantum-state orthogonality equals structural mass orthogonality. For higher modes, the deflation penalty condition is sharpened to a necessary-and-sufficient threshold, with a Davis-Kahan bound quantifying effects of approximate projectors. Numerical studies separate mapping correctness, ansatz expressibility, preprocessing, Pauli growth, finite-shot uncertainty, and damage localization. For 128-DOF chains, consistent-mass whitening increases transformed-operator density from 0.023 to 0.308 and Pauli terms from 576 to 2950. Exact state-vector experiments show qubit count and circuit expressibility are distinct. At 10^5 shots per Pauli term, first-mode frequency RMS error is 2.45%. In an oracle-state study, 10% stiffness loss is localized in 84.5% of trials. Results sharpen the deflation condition, quantify resource bottlenecks, and claim no speedup.

An internal electronic coherence changes electrical transport only when it feeds back on the physical current. We develop a reduced description of this feedback and distinguish its exact consequences from the assumptions required for a microscopic realization. An opposite-parity two-orbital Hamiltonian identifies a current-coupled orbital force. Under an explicitly stated moment closure and collision ansatz, it yields a passive three-state response with an exponentially damped oscillatory memory. The resulting conductivity redistributes a fixed optical weight and predicts a nonmonotonic dependence of dc conduction on coherence damping at fixed remaining parameters. The orbital reduction constrains the coupling and internal frequency through a shared bare splitting, providing a test beyond unconstrained spectral fitting. A charge-conserving spatial extension couples to Maxwell equations through a positive energy balance and separates the constitutive response from longitudinal collective and transverse electromagnetic modes. We formulate complex-conductivity and transmission tests, including the limits of parameter identification over a finite bandwidth. The model supplies a conditional connection between orbital dynamics, transport memory, and electromagnetic observables; conductivity alone does not establish a uniquely quantum mechanism, and a material-specific collision calculation and closure-error assessment remain necessary.

We investigate the dynamics of two-level systems using the quasidistribution $Q$ function projected onto the space of collective measurements. Particular attention is given to evolution under Hamiltonians that are invariant under particle permutations, for pure states that are either invariant or noninvariant under such permutations. This requires constructing an approximate analog of the star product between quasidistribution functions: the projected $Q$ function of a product of two operators is expressed approximately in terms of the individual operators' $Q$ and $P$ functions. We rewrite the Liouville equation to determine approximate state dynamics and compare the result with exact evolution using the Hellinger distance. Overall, the method performs well for permutation-invariant pure states and Hamiltonians, whereas deviations arise for arbitrary pure states and noninvariant Hamiltonians.

Compiling quantum algorithms for real devices involves hard optimization problems that can decide whether an algorithm runs at scale. We present a general method for solving such problems with AI agents, with every result certified. It builds on autoresearch loops, in which agents iteratively improve programs against a fixed evaluator and which have recently improved quantum cryptanalysis circuits, and adds two elements: a frozen, exact verifier certifies every result, and this verifier, together with the challenge around it, is built by an agent that formulates the problem with a researcher and validates the verifier against a solved case, deliberately broken solutions and published results before any solution exists. The method applies to any optimization problem whose solutions can be verified exactly and efficiently. We apply it to three compilation problems in quantum simulation, namely fermion-to-qubit encoding, Hamiltonian layout and unitary synthesis. In each, the agents improved substantially on published or standard constructions, reducing the cost being optimized by up to 73% at the largest sizes tested and outperforming a state-of-the-art optimizer for fermion-to-qubit encodings. Every submission is a program accompanied by its agent's notes, so the ideas behind each improvement are recorded in human-readable form; later agents built on them, and we describe them here. These results open the way to automated, certified discovery across quantum circuit design and beyond.

We develop and analyze generative models based on quantum solvers of stochastic differential equations. Unlike the common approach based on layered variational quantum circuits with parameterized rotations, we parameterize the potential of a Langevin process. The associated Fokker-Planck (FP) equations are Hermitianized and solved using a linear combination of cosine operators implemented through quantum singular value transformation. By encoding the square root of the stationary density, the model enables sampling through computational-basis measurements and is efficiently controlled by coefficients of the block-encoded diagonal potential. We train the proposed model to match empirical distributions within the family described by FP equations, demonstrating parameter recovery for multivariate probability distributions. Crucially, the model remains trainable at scale. Sample-efficient and convex optimization for in-distribution targets arises from a physics-informed inductive bias and holds regardless of the dimensionality of the problem. We provide circuit constructions and efficient block encodings of the main components of the algorithm and analyze resource requirements. Our approach frames quantum generative learning as quantum model discovery and provides a foundation for extending this framework to high-dimensional, strongly correlated scientific data.

Solid state quantum emitters with electronic spin properties can be entangled using optical interferometric which-path erasure techniques that rely on identical frequencies and linewidths of the emitters. This promises a powerful, fast and scalable platform for quantum technologies. Using current protocols, a pair of emitters embedded in a waveguide interferometer can be deterministically prepared in a maximally entangled state. However, the amount of entanglement diminishes rapidly with increasing separation of the emission lines and variations in the linewidths of the emitters. Solid state emitters such as quantum dots are subject to intrinsic variations in the fabrication process. Therefore, manufacturing the required number of identical emitters on a chip is not scalable. In this Letter, we present a method that uses readily available pairs of entangled photons to entangle solid state emitters with large transition frequency separations and linewidth variations, circumventing the need to fabricate optically identical emitters. We demonstrate a concurrence of C = 0.95 for typical quantum dots using narrowband photon inputs.

We consider finite-dimensional non-Hermitian systems in which all modes coalesce at a single exceptional point. For a rank-one anti-Hermitian contribution, the spectral response strength is computed exactly. For passive systems, we then derive a sharp upper bound at fixed exceptional-point decay rate and show that it is reached only when the decay operator has rank one, corresponding to a single independent dissipative direction. This establishes rank-one loss as the optimal configuration for enhancing the response of a full-order exceptional point. The bound holds for arbitrary order and improves on earlier passive estimates beyond second order. Two third-order trimers illustrate the result: a rank-one-loss system saturates the bound, whereas a passive rank-two-loss realization remains below it. The result turns dissipation into a design resource: concentrating the loss into a single effective dissipative direction maximizes the highest-order spectral response of a passive full-order exceptional-point device.

Projected quantum kernels (PQKs) have emerged as a notable approach to circumvent the hardness of machine learning tasks arising from the exponential dimensionality of the quantum Hilbert space. However, recent PQK studies often rely heavily on extensive classical hyperparameter tuning of the radial basis function (RBF) kernel parameter and the support vector machine regularization parameter. The extensive tuning can mask the true representational power of the underlying PQKs induced by quantum feature maps, which has not been explored in detail. Thus, this work aims to expose the structural capabilities of PQKs by isolating and evaluating their native inductive bias through comparisons between untuned and tuned PQKs against the RBF baseline. Furthermore, we propose novel quantum feature maps that leverage two-qubit entanglement to capture multivariate correlations in IoT data. The results show that extensive tuning can lead to competitive performance architectures, while our proposed entanglement topologies exhibit a significantly stronger native inductive bias. This reveals that superior quantum architectural design can yield structurally better PQKs with improvements arising from quantum-mechanical properties rather than from classical hyperparameter tuning.

Quantum metrology is ultimately shaped not only by measurements, but also by the dissipative dynamics that prepare and maintain the probe. Nevertheless, a general mechanism for enhancing both steady-state and transient precision in open quantum systems has been lacking. Here we show that adding a simple reset channel provides such a mechanism: reset acts as a minimal dissipative control that can enhance metrological precision without modifying the intrinsic Hamiltonian or applying continuous coherent driving. We derive a unified quantum-Fisher-information (QFI) reset-rate response identity, showing how reset enhances steady-state and transient estimation while revealing a sharp transient distinction. For static-parameter estimation in diagonal dynamics, reset leaves the leading short-time QFI unchanged; for the separate task of elapsed-time estimation, it generates an immediate drift contribution that can scale quadratically with the reset rate in the short-time limit. For frequency estimation, the enhancement is instead dominated by a genuinely quantum eigenvector contribution. These results establish reset as a simple dissipative resource for open-system quantum metrology.

The implication of entanglement in quantum battery charging remains poorly understood. In addition, intrinsic quantum randomness poses a fundamental challenge to charging uniformity across distinct trials. To address these issues, we study a three-qubit system within a cascaded collision frame, with two qubits acting as the charger and the third serving as the battery. After each collision, an adaptive measurement is performed on the charger, yielding four conditional post-measurement battery states with identical expected stored energy. For arbitrary fixed charger states, we derive analytical expressions for the recurrence relation of stored energy. We find that stored-energy fluctuations depend on whether the dynamics relies on the battery phase \(γ_n\). For two Bell-like families of entangled states, together with their computational basis states termed Bell-like separable states, the dynamics is \(γ_n\)-independent and fluctuations vanish, whereas for other entangled and separable states, fluctuations emerge. These insights establish a paradigm for engineering charger states to design uniform-charging quantum-battery architectures despite inherent quantum randomness.

Local pure dephasing suppresses single-spin coherence, yet we show that it sustains continuous time-crystalline order in a fully connected ferromagnetic spin-$1/2$ ensemble with local decay. An exact operator identity reveals the mechanism: dephasing raises the interaction energy, while energy relaxation on a finite timescale converts this charging into delayed feedback. Within homogeneous mean-field theory, we prove that dephasing is necessary for periodic motion in this model and that feedback exactly balances transverse damping over each cycle. Beyond mean field, the identity fixes the relative amplitude and phase of energy and longitudinal magnetization in oscillatory Liouvillian modes. Liouvillian spectra and stationary two-time correlations characterize temporal order through decay rates that decrease algebraically with system size, frequencies approaching nonzero mean-field values, and comparable per-spin oscillatory weights. Semiclassical trajectories further reveal recurrent switching between a limit-cycle region and two symmetry-related stationary regions: fluctuations interrupt and reactivate collective oscillations, and oscillatory episodes provide an intermediate channel between stationary regions. These results establish local dephasing as a resource for autonomous collective motion and show how the resulting temporal order can participate in metastable dynamics.

The emergence of entangled quantum optical states in high-harmonic generation raises a fundamental problem about its characterization, namely, \textit{how can entanglement of extreme-ultraviolet radiation be certified for attosecond light fields?} Here, we provide experimentally accessible separability tests, particularly showing that attosecond photoelectron interferometry provides a direct solution to this problem. This is achieved by a quantum optical treatment of mapping photoelectron interferometry to the measurement of optical correlation functions. This yields a negative-partial-transpose witness for infrared-XUV entanglement and a sufficient witness of genuine multipartite entanglement without auxiliary optical measurements. We evaluate both witnesses on explicit optical states and identify how the protocol can be extended to XUV-XUV entanglement certification. Hence, we establish attosecond photoelectron interferometry as a general framework for entanglement certification across a wide range of optical frequencies.

Ultracold quantum gases offer a controllable and microscopically accessible platform for understanding and engineering superfluidity. Yet, realizing a superleak that selectively transports the superfluid while suppressing normal flow has remained elusive. Here, we harness an optical superlattice to realize such a superleak through dynamical selectivity. The superfluid undergoes coherent Josephson transport, whereas the normal component exhibits slow, thermodynamically limited response, resulting in a flow-rate contrast of 500(49). Exploiting this contrast, we demonstrate repeated filtering of the normal component and dynamical purification of the superfluid, while sustaining coherent driven oscillations for up to 100 cycles. Our results establish a controllable atomic superleak and open possibilities for manipulating transport and thermodynamics in quantum fluids.

We propose Quantum Constrained Hamiltonian Descent (QCHD), a continuous-time quantum framework for optimization under smooth equality constraints. The unconstrained counterpart, Quantum Hamiltonian Descent (QHD), minimizes a cost function by simulating the Schrödinger dynamics of a particle in the potential given by the cost function. Applying Dirac's formalism to the classical dynamics with constraints, we construct an intrinsic quantum Hamiltonian with a Laplace--Beltrami operator on the constraint manifold in a kinetic term. Its evolution preserves the constraints exactly without penalty terms and is expected to solve quantum-dynamically the constrained optimization problem. We analyze its relation to Quantum Hamiltonian Descent supplemented by a strong penalty term. For a squared-distance penalty, the effective tangential dynamics acquires an extrinsic-curvature potential and, in nontrivial normal-rotation sectors, a coupling to the normal-bundle connection. These embedding-dependent terms remain in the strong-penalty limit, generally yielding quantum dynamics different from QCHD. Numerical comparisons for circular, elliptical, and two simultaneous constraints show faster optimization and improved concentration near global minima for the initial states and finite penalty strengths considered.

Formulated a hundred years ago, the Bridgman formula for thermal conductivity of liquids postulates a proportionality between sound velocity and thermal conductivity. This designates phonons as heat carriers in a liquid. Its empirical success has been under-appreciated and its conceptual implications overlooked. It is not mentioned in well-known condensed-matter textbook. Here, we review its origin, its links to hydrodynamic Euler equations and to the fundamental paradox surrounding the parabolic heat equation and its fate across the quantum-classical crossover.

Magic-state factories are a major cost of fault-tolerant quantum computing, yet how few noisy inputs they need is known only for restricted protocols. We show that, for tolerating input faults, any stabilizer protocol, however adaptive, postselected or multistage, is no better than a projection onto one stabilizer code, and that for rational targets a fault pattern is harmful exactly when its complement is. Searches over all codes show that quadratic distillation of one T state needs exactly nine inputs and that the eight-input CCZ factory is optimal. At order $d$, one T state needs $n\geq2d$.

With the target of efficiently solving the quantum-mechanical Schrödinger equation on future quantum computers, first- and second-order product formulas for the time-evolution operator are proposed, designed to exploit hierarchies in the operator norms of the individual Hamiltonian components. Inspired by the THRIFT product formula, these decomposition schemes achieve a suppression of the leading error term by a factor of alpha<1 with respect to the standard Lie--Trotter--Suzuki splitting of the same order, where alpha quantifies the norm ratio between the dominant and subdominant parts of the Hamiltonian. Unlike THRIFT, the proposed formulas retain the general product-formula structure, making them applicable to Hamiltonians whose terms act on an arbitrary number of qubits. The advantages of this approach are demonstrated through numerical experiments on engineered two-dimensional spin-1/2 XY model systems and isolated molecules within the double-factorization framework.

Scale-free localization is a distinctive phenomenon in non-Hermitian systems, where specific eigenstates, known as scale-free localized states (LSs), possess localization lengths that scale linearly with the system size. Here, we show that a single non-Hermitian defect in one-dimensional quantum walks (QWs) induces scale-free localization. Driven by non-Hermiticity, the QW system undergoes a pseudo-Hermitian (PH) phase transition and the PH symmetry breaking is accompanied by the emergence of scale-free localization. As non-Hermiticity is further increased, the system undergoes a second phase transition, marked by the emergence of two pairs of bound states. Crucially, we identify the critical points of both transitions using localization properties. Furthermore, we extend our investigation to two-dimensional QWs, where a single non-Hermitian defect also induces scale-free localization, thereby demonstrating the universality of this phenomenon. Our work provides a valuable perspective for further exploring defect physics and a type of novel LS in non-Hermitian quantum systems.

We present an organizing framework for concatenated quantum error correction based on the observation that the syndrome projection of a stabilizer code reshapes the noise channel in a code-determined manner. For any stabilizer code, one level of QEC maps the physical noise to a block-diagonal logical channel whose diagonal Pauli weights are fixed by the code geometry. Coherences between different syndrome classes vanish, and no physical Pauli twirl is required to reach this block-diagonal form. Concatenation can then be viewed as the iteration of the same redistribution step: the dominant logical error after one level selects the code used at the next. We instantiate the framework with the two smallest stabilizer codes, the bit-flip and phase-flip codes, and apply it to amplitude damping. The redistribution rules give the concatenation protocol $C_2(\hatσ_y) C_1(\hatσ_x)$, whose ideal-recovery fidelity scales as $f_l=1-\mathcal O(γ^2)$. Solving the crossover condition $F_l>F_{l-1}$ in the ideal-gate limit yields a critical damping parameter $γ_c\approx0.30$; in terms of the initial channel fidelity, $f=1-1.72755γ^2$. Under the same ideal-recovery assumption, we compare the overall gate accuracy rate with that of the five-qubit code. The scope of the framework, in particular for coherent and correlated noise, is stated explicitly.

This oral history interview provides Yakir Aharonov's personal and conceptual recollections from the 1950s to the 2000s, focusing on his academic trajectory, some of his major contributions to quantum foundations, and his perspective on the development of the field. The interview traces Aharonov's academic career through the Technion, University of Bristol, Brandeis University, Yeshiva University, University of South Carolina, Tel Aviv University, George Mason University, and Chapman University. The interview also traces the development of Aharonov's work and collaborations on the EPR paradox, time-energy uncertainty relations, quantum measurement theory, quantum frames of reference, the two-state vector formalism, weak values, protective measurements, and several other contributions. It includes recollections of meetings and discussions with David Bohm, Niels Bohr, John Clauser, Paul Dirac, Rudolf Peierls, Aage Petersen, and Abner Shimony. Also mentioned: David Albert, Jeeva Anandan, Peter Bergmann, Gideon Carmi, Avshalom Elitzur, Dave Finkelstein, Vladimir Fock, Itzhak Kalugai, Ed Lerner, Joel Lebowitz, Stanley Mandelstam, Yuval Ne'eman, Sandu Popescu, Maurice Pryce, Daniel Rohrlich, Nathan Rosen, Joseph Safko, Paul Singer, Daniele Struppa, Leonard Susskind, Lev Vaidman, Chien-Shiung Wu.

We demonstrate a monolithic telecom C-band single-photon platform based on low-density InAs/InP quantum dots grown on an InGaAsP/InP distributed Bragg reflector, with simulated upward light-extraction efficiency exceeding 10% within the 40 nm spectral band. Enhanced light extraction is crucial for wide-field photoluminescence imaging, enabling approximately 3 nm statistical centroid-localization precision of QD emitters due to improved signal-to-noise ratio. The identified charged exciton emitting at 1549.5 nm exhibits single-photon emission purity up to 94.7%, validated by a raw peak-area integration under pulsed quasi-resonant excitation. Under these conditions, photons emitted sequentially from the unprocessed planar structure reveal a raw two-photon interference visibility of 51% of the photon wave packet within the 2 ns time window and 41% over a 4 ns integration window, all without Purcell enhancement typical for cavity-embedded emitters. Combining broadband extraction, high photon coherence, and emitter preselection on a native III-V wafer, this architecture paves the way for marker-based deterministic fabrication of high-quality monolithic nanophotonic devices.

We first prove a sharp Lieb-Thirring inequality with semi-classical constant and gradient correction in one dimension. In the periodic setting, the corresponding inequality also includes a parity dependent shell-correction term, which appears to be new. Moreover, we also characterize the optimizers of these inequalities. In particular, the optimizing density profiles form a two-dimensional manifold, which we call here the Poincaré density manifold. We then apply these results to study the Thomas--Fermi--von Weizsäcker (TFW) approximation of the kinetic energy in Density Functional Theory. More precisely, we first obtain an explicit and non-asymptotic bound on the global and local error made by the TFW approximation. These bounds are controlled by the distance of the normalized density profile from the Poincaré density manifold times the number of particles. In particular, these bounds show that the TFW approximation is exact on the Poincaré manifold. We then show that, in the periodic setting, the distance between the Kohn-Sham potential and the inverse TFW potential in the natural dual Sobolev space can also be controlled by explicit density dependent constants times the distance to the Poincaré manifold. As a corollary, we prove that for a fixed density profile, the Kohn-Sham potential converges towards the inverse Thomas--Fermi potential in the high-density limit $N \rightarrow \infty$ with asymptotic rate of order $N^{-2}$. This rate is shown to be optimal.

Millimeter-wave and terahertz technologies offer new opportunities for high-capacity communications, sensing, and quantum systems, but electronic signal chains above 100 GHz are limited by weak sources, noisy receivers, and lossy interconnects. Photonic approaches mitigate these constraints by enabling chip-scale high-frequency components, yet existing implementations generally retain lossy off-chip electrical or free-space links, hindering dense and compact integration for cryogenic or space-constrained settings. Here, we show a monolithic lithium tantalate photonic chip, termed a signal core, which generates, modulates, routes, and detects continuous-wave signals at discrete frequencies between 100 GHz and 2.5 THz. The architecture integrates high-frequency functional modules on chip and uses exclusively fiber-based optical interfaces. Bidirectional coherent electro-optic conversion enables signal generation, detection, and nanosecond-scale amplitude and phase modulation, while micro-coplanar striplines interconnect the modules into an end-to-end signal chain on a single chip. Our modules achieve single-photon electro-optic coupling rates of g_0/2π=10 kHz and peak drive-power-normalized photon-flux conversion efficiencies of 1.0%/mW for generation and 0.5%/mW for detection. It also operates at 4 K in a dilution refrigerator through the same fiber-only optical links. Together, these capabilities establish an all-photonic platform for millimeter-wave-to-terahertz systems and offer a broadly applicable architecture for applications constrained by electrical-interconnect loss, heat load, and footprint.

The rate operator quantum jumps (ROQJ) is a general method to unravel a master equation describing the dynamics of an open quantum system into stochastic pure state trajectories. By post-selecting on no jumps occurring, one obtains a trajectory generated by a non-Hermitian Hamiltonian. The ROQJ allows for versatile modification of this non-Hermitian evolution, with each non-Hermitian Hamiltonian corresponding to a different continuous measurement scheme. We apply the ROQJ to modify the non-Hermitian dynamics of the open three-particle Bose-Hubbard dimer model under environmental non-local dephasing to construct a $PT$-symmetric non-Hermitian Hamiltonians with a general two parameter $PT$-symmetric imaginary diagonal part, which generalizes the well-known gain-loss Bose-Hubbard dimer. We characterize the symmetry structure of the spectrum for different on-site interaction strengths. For vanishing on-site interaction, we find the unbroken $PT$-symmetry region enclosed by order two exceptional lines of different character and four order four exceptional points, two of which are not found in the usual gain-loss Bose-Hubbard dimer. Additionally, we find regions with degenerate imaginary parts of the eigenvalues, also not found in the gain-loss Bose-Hubbard dimer. In this parameter space, we use time-dependent rate operator transformations to investigate state transfer under slowly varying parameter loops. Loops encircling an order four exceptional point exhibit chiral state transfer. Because the loops cross exceptional lines, the final states are superpositions of eigenstates. Chiral state transfer is also found with non-zero homogeneous on-site interaction when the loop crosses over broken $PT$-symmetry regions of different character. Using inhomogeneous on-site interactions, we find direction dependent state transfer between eigenstates without crossing or encircling exceptional points.

Port-based teleportation (PBT) is a variant of quantum teleportation that does not require corrections on the teleported state: starting with $N$ shared EPR states, Alice can teleport a qudit to Bob by performing a measurement on her system and informing Bob which of his $N$ `ports' to retrieve the state, up to infidelity decaying with $N$. Existing quantum circuits of PBT rely on representation theory tools and the mixed Schur transform. In this note, we report an elementary efficient circuit for PBT, which has depth $\operatorname{polylog}(N,d)$. As a corollary, this gives a simple proof that all $n$-qubit unitaries can be parallelized to $\operatorname{poly}(n)$ depth, recovering a recent result due to Nehoran--Slote--Yuen and OpenAI.

Lattice-surgery compilation places logical qubits on a grid of surface-code tiles and routes their interactions. Sparse static layouts limit routing contention but reserve space that often remains idle. Reducing this reservation requires balancing area savings against additional gate serialization and qubit movement. In this paper, we present a co-designed dynamic architecture and compiler that allocates routing space according to circuit demand. The architecture preserves a fixed virtual qubit floorplan while allowing its physical spacing to change between execution stages. The compiler coordinates placement, scheduling, and routing to implement lattice surgeries using fewer physical qubits. Across our application benchmarks, our method reduces space-time volume by 55.6% in geometric mean and compiles 75.5 times faster than the evaluated DasCot configuration. A circuit-synthesis case study shows how our compiler exposes optimization tradeoffs.

The elementary charged excitations of fractional quantum Hall states are anyons. Without continuous translation symmetry, they acquire a dispersion and richer dynamics. We study the Laughlin quasihole at filling $1/3$ in a periodically modulated magnetic field, a common model of fractional Chern insulators in two-dimensional materials. From the microscopic wave functions, we derive the commutator of its guiding-center coordinates, set by a many-body Berry curvature that governs its wave packets. A modulation with two flux quanta per unit cell splits the quasihole band into bands with Chern numbers $6$ and $-3$; such opposite signs are generic as long as a weak modulation opens a gap between the anyon bands. In the $C=-3$ band, the quasihole drifts against $\mathbf{E}\times\mathbf{B}$, although the magnetic field has the same sign everywhere. Perturbation theory in the modulation explains these results, and large-scale Monte Carlo calculations confirm them. Anyon bands thus acquire their own topology, which controls anyon motion and may shape the phases of itinerant anyons.

We investigate quantum-enhanced time-reversal-based metrology using the central spin model, in which a single ancilla spin of magnitude $S_{\rm cen}$ mediates interactions between $N$ bath spins through a star-graph topology. We demonstrate that the SATIN (Signal Amplification Through Time-reversal Interaction) echo protocol can be implemented in this setup to achieve a Fisher information of $N^2/e$ with the collective $\langle J_y\rangle$ readout, corresponding to a $4.34\,\mathrm{dB}$ offset from the Heisenberg limit. Furthermore, we establish that this platform provides a pathway to perform the butterfly echo protocol by conjugating each evolution step with a random collective bath rotation, thereby achieving axis-agnostic Heisenberg-scaled sensing. Crucially, with a small $N-$independent number of random steps, the butterfly echo reaches a Fisher information of $N^2/4$ ($6\,\mathrm{dB}$ below the Heisenberg limit) for any unknown encoding axis, with the plateau gain tracking the Haar limit. Finally, we demonstrate that the central-spin magnitude $S_{\rm cen}$ provides a powerful knob to reduce the optimal protocol timescale without altering the metrological ceiling or the circuit depth required to reach isotropy. The proposed scheme is relevant to cavity QED and NMR quantum processors, where the central spin architecture arises naturally.

In the companion paper (Part I), we developed an optimal-control framework to suppress intrinsic and decoherence-induced errors in controlled-Z (CZ) gates between directly coupled, frequency-tunable transmons. Here, we extend this framework to incorporate uncertainties in coupling strength, anharmonicities, and zero-flux qubit frequencies, enabling the design of high-fidelity gates robust against noise and parameter uncertainties. We classify these uncertainties by whether they perturb the off-diagonal coupling strengths or the diagonal detunings of the Hamiltonian, and we identify distinct suppression mechanisms for each class. Coupling errors are mitigated through dynamical decoupling induced by strong detuning modulation. For a 30-ns gate, this strategy reduces the coupling error to $6.21\times10^{-7}$ and tolerates coupling-strength uncertainties up to $2π\times4$ MHz while keeping total gate infidelity below $10^{-3}$. Detuning errors are minimized near a symmetric-detuning operating point that balances the two dominant leakage-mediated interactions. A 24-ns gate operated near this point tolerates individual uncertainties of up to $2π\times5$ MHz in each relevant diagonal parameter under the same infidelity threshold. We further optimize gate performance under realistic conditions where intrinsic errors, decoherence, and parameter uncertainties coexist across six representative stages of progressively improving hardware performance. The resulting stage-specific controls achieve lower infidelity and greater robustness. Together with the companion study (Part I), this framework offers a practical approach to balance speed, fidelity, and robustness while reducing the need for exhaustive characterization and frequent recalibration in large-scale superconducting quantum processors.

Quantum key distribution (QKD), whose security is derived from quantum mechanics rather than computational assumptions, is moving into standardization and commercial deployment. Yet its security guarantees rest on technically delicate proofs checked by hand. Formal verification closes this gap, establishing a two-factor assurance: unconditional security from physical principles, and machine-checked proofs against reasoning errors. We present FVQKD, a Rocq library for machine-checking QKD security proofs. Its first result is a complete, end-to-end machine-checked proof of composable, finite-key security for BB84. The mechanization reconstructs the complete proof infrastructure from first principles, including the smooth entropy framework, the entropic uncertainty relation, and the Quantum Leftover Hash Lemma. It uncovers necessary side conditions that the published argument leaves unstated, one of which reveals a missing proof branch, and it grounds the information-theoretic bound in a formal semantics of protocol execution, which the pen-and-paper analysis lacks. The proof is entirely admit-free, relying only on the Rocq kernel and standard foundational axioms. To our knowledge, this is the first end-to-end formal verification of a QKD security proof. Built on MathComp, MathComp-Analysis, and CoqQ, the development provides quantum-information infrastructure designed for reuse across broader QKD variants and quantum cryptography applications.

Set coherence and set imaginarity are two important quantum resources defined by sets of states. We investigate tuples of qubit states under vanishing higher-order Bargmann invariants and show that their set coherence and set imaginarity are each related to whether they contain a pair of orthogonal states. Specifically, when the relevant higher-order Bargmann invariants vanish, the tuple contains a pair of orthogonal states if and only if removing some state makes the remaining tuple incoherent. Moreover, when maximally mixed states are excluded, the same vanishing conditions imply that the tuple is imaginarity-free if and only if it contains a pair of orthogonal states. As a consequence, under these conditions, a tuple of single-qubit states has imaginarity precisely when every tuple obtained by deleting one of its states is coherent.

The purpose of this paper is to conduct a comprehensive structural analysis of quantum finite-level systems in the Heisenberg picture, where the evolution of system observables is modeled by bilinear quantum stochastic differential equations (QSDEs). Firstly, real coordinate transformations that preserve commutation and anticommutation relations are characterized, and relative admissibility between different orthonormal Hermitian bases is formulated. Secondly, strongly aligned subspaces are introduced, based on which decoherence-free subsystems (DFSs) are constructed in general orthonormal Hermitian basis as well as the generalized Gell-Mann basis. Thirdly, conditions for the existence of quantum nondemolition (QND) variables are given in terms of both linear systems theory and spectral separation by output-signal observables. Finally, a sufficient condition for quantum back-action-evading (BAE) measurements is established. A four-qubit nearest-neighbor Heisenberg chain with collective dephasing illustrates these structural properties of quantum finite-level systems.

Excess micromotion induced by stray DC electric fields limits the control fidelity of trapped-ion experiments. Various techniques have been developed to detect and compensate ion displacements from the RF null by monitoring modulated fluorescence, ion positions, or micromotion sidebands. Although these approaches are effective, they do not probe the displacement through a ground-state-cooled motional mode and therefore offer limited compatibility with quantum-enhanced sensing protocols. Here, we demonstrate a micromotion compensation method based on the driven coherent amplitude of a ground-state-cooled motional mode. In this approach, the ion displacement is converted into a coherent motional excitation by an auxiliary RF drive and detected through the qubit. We determine the optimal compensation field with a $1σ$ statistical uncertainty of 8 mV/m. The method is naturally compatible with quantum-enhanced sensing protocols employing nonclassical motional states, including Fock, squeezed, and Schrödinger-cat states, providing a pathway toward quantum-enhanced micromotion compensation.

We investigate a hierarchy of invariant Hilbert-space structures connecting Hilbert-space fragmentation, partial solvability, and quantum many-body scars. For spin chains with fragmented spin-$1/2$ subspaces and their local deformations, we show, using the spin-$1$ $XXC$ chain as a representative example, how successive local deformations reduce extensive irreducible-string fragmentation through an implicitly embedded spin-$1/2$ invariant space and ultimately to a single scar tower, connecting the $XXC$, perturbed $XXC$, and spin-$1$ $XY$ scar models. Through the intermediate embedded space, local dynamics couples states from distinct frozen irreducible-string sectors and selects a new decomposition into representations, from which smaller invariant spaces can be retained. We also establish a rigidity constraint on isolating nonsymmetric towers and a constructive correspondence that transfers a reduction between locally realizable representations of the embedded dynamics. The latter demonstrates that the reduction hierarchy can be transferred through a unitary transformation within the embedded subspace, yielding an exact scar tower built on a Néel reference state without requiring unitary equivalence of the full Hamiltonians.

We present the conditions for satisfying the cluster property in the superconducting state. Using these conditions, we show that the cluster property employed when deriving the order parameter of the superconducting state (OPSS) holds true, and that the OPSS is given by ${}_S\langle Ψ| \hatψ(x)\hatψ(x') | Ψ\rangle_S$, where $|Ψ\rangle_S$ is the superconducting state, and where $\hatψ(x)$ is the field operator of superconducting electrons. This provides a resolution to the long-standing concern raised by Leggett et al.\ regarding particle-number fluctuation in the superconducting state. In addition, by considering the entanglement between two particles composed of the maximum geminal of the BCS ground state [J.\ Phys. Commun. 5, 095003 (2021)], it is confirmed that the larger the deviation from the conditions for satisfying the cluster property becomes, the greater the magnitude of the entanglement becomes. This shows not only the effectiveness of the conditions for satisfying the cluster property but also the justification of the OPSS that has been commonly used.

Quasiperiodic systems combine sharply different spectral and localisation regimes with a dense hierarchy of dynamical time scales. We show that a finite-rate quantum Otto cycle can use this structure as a thermodynamic probe, revealing which parts of the spectrum become dynamically accessible and thermodynamically relevant during a driven transformation. For a generalised Aubry-André-Harper chain, the resulting response is not determined by the static quasiperiodic regime alone: extended, near-critical, and crossing protocols do not exhibit universal ordering of work fluctuations. Instead, the statistics reflect transition pathways that are simultaneously dynamically coupled, thermally occupied, and energetically significant. The same spectral accessibility separates thermodynamic recovery from microscopic adiabatic recovery. Positive mean work can reappear while the population transfer dynamics remain strongly nonadiabatic because finite-rate population transfer is redistributed toward energetically less costly channels rather than suppressed. The full work distribution reveals a further separation, with a finite rate window in which positive-work cycles form a majority although the mean work remains negative. This behaviour persists in finite-size analysis. A thermally weighted spectral susceptibility connects these effects to a distributed hierarchy of dynamically active spectral regions rather than to a single minimum-gap bottleneck. Finite thermal contacts preserve this picture while introducing a second time scale and intercycle memory. Quantum Otto cycles can therefore provide a fluctuation-resolved thermodynamic probe of quasiperiodic spectral accessibility, complementary to direct spectroscopic and eigenstate-resolved diagnostics.

Insider Brief Plurilock shareholders will vote Nov. 18 on a proposed acquisition by Quantum eMotion that would combine quantum-based security technologies with Plurilock’s cybersecurity operations and customer network. Shareholders would receive C$0.084 in cash and 0.0763 Quantum eMotion shares for each Plurilock share, implying an offer value of C$0.28 per share. Plurilock’s board recommends approval, with completion expected in late November subject to shareholder, court and other required approvals. Plurilock Security shareholders will vote Nov. 18 on a proposed acquisition by Quantum eMotion , a deal intended to pair quantum-based security technology with an established cybersecurity business and its customer network. Plurilock said in a news release that it has filed and mailed documents explaining the transaction ahead of a special shareholder meeting in Vancouver. The companies expect to complete the acquisition in late November if shareholders, the court and other authorities approve it. The announcement marks another step toward completing the proposed purchase, rather than a completed acquisition. Under the agreement, Quantum eMotion would acquire all outstanding Plurilock common shares. Shareholders would receive C$0.084 in cash and 0.0763 of a Quantum eMotion share for each Plurilock share they own. For example, an investor holding 1,000 Plurilock shares would be entitled to C$84 in cash and 76.3 Quantum eMotion shares before any provisions governing fractional shares. The companies put the implied value of the offer at C$0.28 per Plurilock share. Because the payment includes stock, its value will depend partly on Quantum eMotion ’s share price. The agreement specifies how many Quantum eMotion shares investors would receive, rather than guaranteeing a fixed cash value for that portion. A Route to Customers The business rationale centers on bringing Quantum eMotion ’s technology to more customers through Plurilock’s existing sales and service operations,

Insider Brief Toshiba launched its Quantum-Safe Networking Platform to help organizations protect critical data connections and expand coverage across existing network infrastructure. The platform combines post-quantum cryptography, quantum key distribution and quantum random number generation with centralized network control and key management. Toshiba says optical switching, integrated transceivers and shared-fiber capabilities reduce equipment requirements and deployment costs, with a single hub able to serve hundreds of remote sites. PRESS RELEASE &#8212; Toshiba Corporation today announced the launch of its Quantum-Safe Networking (QSN) Platform, marking a major step towards delivering true scalability, flexibility and greater efficiency in the deployment of quantum-safe networks. The Toshiba QSN Platform brings together interoperable equipment and deployment capabilities within a unified architecture. It is designed to help network operators, data center service providers, enterprises and public-sector organizations protect their most critical data paths first and expand as their security, operational and commercial requirements evolve. Importantly, those organizations do not need to rebuild their networks to get started. The platform integrates with existing network infrastructures and can support deployments from a single dedicated connection to large metro, hub-and-spoke, ring, mesh and long-distance networks.&nbsp; By simplifying the deployment of quantum-safe networks and improving the economics of expanding across multiple sites, the platform helps turn the quantum-safe transition into a strategic advantage. Organizations can strengthen network resilience while scaling protection in line with their needs. Service providers can also begin to offer differentiated quantum-safe services to create new revenue opportunities. The quantum-safe transition is under way The prospect that sufficiently powerful quantum computers could render many of today’s encryptio

Insider Brief Researchers from Rutgers , IBM and collaborating institutions demonstrated real-time quantum feedback on up to 100 qubits, using repeated measurements and resets to control chaotic behavior. The experiment used a 156-qubit IBM Heron processor to perform nearly 5,000 two-qubit operations and nearly 5,000 measurements and resets while the system continued running. The researchers observed a sharp transition from chaos to control when resets outpaced scrambling, confirming theoretical predictions and demonstrating a capability needed for future fault-tolerant quantum computers. PRESS RELEASE &#8212; Researchers from Rutgers , IBM and collaborating institutions have shown that a quantum computer can check what is happening inside it and respond while it is running, repeatedly resetting parts of the system to bring chaotic behavior under control. The advance is a critical step toward building larger, more reliable quantum computers.&nbsp; Today’s quantum computers operate according to the unusual rules governing atoms and other extremely small particles. They could one day solve problems beyond the reach of conventional computers — designing better batteries and cleaner industrial catalysts, simulating molecules and materials too complex for today’s computers, and running certain artificial intelligence programs. In a study published in Nature Physics , researchers from Rutgers , International Business Machines Corp., and collaborating institutions showed that a quantum computer can repeatedly check and reset parts of itself while running. The experiment is among the largest demonstrations to date of real-time quantum feedback control, a capability considered essential for future quantum computers that will be fault tolerant. Scaling quantum computers will require them to identify and correct errors while they are working, a capability known as error correction, which will allow for the construction of a fault-tolerant quantum computer.&nbsp;A fault-toleran

For the first time, Northwestern University physicists have coaxed a single positron—the antimatter counterpart of an electron—into an exquisitely controlled quantum state.

Scientists from the Quantum Technologies Group at the Institute of Physics Zagreb, in collaboration with a colleague from the Physics Department at the Faculty of Science (PMF), have experimentally demonstrated for the first time the existence of discrete one-dimensional (1D) solitons in an optically induced photonic lattice in warm rubidium vapor.

Quantum networks, systems that connect devices and allow them to exchange information encoded in the quantum states of particles, could enable more secure communications. To build these networks, physicists need to devise strategies that allow distant particles to share quantum states, preserving them long enough to perform calculations or enable communication between devices.

Insider Brief Vulcan Elements is partnering with the North Carolina Collaboratory and UNC-Chapel Hill to develop higher-performance rare earth magnets for defense and commercial applications. Supported by a $600,000 research award, the team will use quantum-mechanical simulations to predict how atomic-level changes affect magnetic properties. Vulcan’s factory under construction in Benson, North Carolina, is planned to produce 10,000 metric tons of magnets annually and create 1,000 manufacturing jobs. Vulcan Elements, an American rare earth magnet manufacturer, today announced a partnership with the North Carolina Collaboratory to advance the development of high-performance rare earth magnets for critical defense and commercial technology applications.&nbsp; The collaboration brings together Vulcan Elements and leading scientific expertise at the University of North Carolina at Chapel Hill (UNC-Chapel Hill), where research led by chemistry professor Yosuke Kanai, PhD, will develop a novel analytic capability using quantum-mechanical simulations to predict with significant accuracy how changes at the atomic level affect magnetic properties, ultimately setting a new standard for Vulcan&#8217;s magnetic performance. The partnership represents a convergence of two research fields that are foundational to national security and the future economy: rare earth magnets and quantum mechanics. The research will pair Kanai&#8217;s more than 25 years of experience in computational materials research with Vulcan Elements&#8217; expertise in manufacturing rare earth magnets. The Collaboratory is supporting the partnership through a $600,000 research award, helping support the application of UNC-Chapel Hill&#8217;s scientific expertise to advance rare earth magnet innovation. Established by the North Carolina General Assembly in 2016, the Collaboratory works with academic experts across the state to transform research into practical applications for the benefit of North Carolina. Si

Insider Brief The National Physical Laboratory (NPL) has secured Government Office for Technology Transfer (GOTT) funding to advance trapped-ion quantum computing technology , with a focus on manufacturing scalability. The project will develop a batch packaging process for ion-trap devices to address production yield and manufacturing bottlenecks that limit large-scale production. The work aims to support reliable manufacturing of ion traps for networked quantum computing architectures, building on NPL technology already used at NPL, the University of Oxford and the National Quantum Computing Centre. PRESS RELEASE &#8212; The National Physical Laboratory (NPL) has secured funding through the Government Office for Technology Transfer (GOTT) to accelerate the development of next-generation trapped-ion quantum computing technologies, helping address one of the sector&#8217;s most significant barriers to commercial adoption: scalability. Quantum computing has the potential to transform industries by solving complex problems that are beyond the reach of today&#8217;s most powerful classical computers. Rather than relying on conventional binary transistors, quantum computers use quantum bits, or qubits, which exploit the principles of quantum mechanics to perform calculations at unprecedented speeds.&nbsp; Trapped-ion systems have emerged as a leading platform, among competing quantum computing technologies being developed worldwide, due to their exceptional fidelity, stability and scalability. NPL plays an important role this field, having developed a microfabricated, chip-scale ion microtrap capable of confining and manipulating arrays of ions. The technology provides a highly scalable architecture that is ideally suited for quantum computing and quantum networking applications. NPL&#8217;s ion microtrap devices are already supporting cutting-edge research activities at both NPL and the University of Oxford. Building on this success, a previous GOTT Knowledge Asset Gran

How hybrid infrastructure is making quantum commercially actionable today – and why the organizations building that infrastructure now will be the ones ready when the hardware arrives. Insider Brief Quantum readiness is an infrastructure problem as much as a hardware one: organizations are in a &#8220;prepare for quantum&#8221; era, and integrating isolated quantum processors with enterprise IT through secure, low-latency interconnection is the step most organizations are overlooking. Paris-based Qubit Pharmaceuticals shows this approach in practice. Its four-layer ATLAS platform combines polarizable molecular dynamics, a synthetic quantum chemistry data engine built with Sorbonne University, the FeNNix-Bio1 foundation model, and the Hyperion-1 emulator, which simulates up to 40 qubits on classical hardware. Quantum advantage has not yet been demonstrated in drug discovery, but the milestones that matter now (algorithm validation, workflow integration and ecosystem maturity) don&#8217;t require fault-tolerant hardware. Organizations that delay preparation risk falling further behind as a result. The Era Between Eras The prevailing assumption about quantum computing is that fault-tolerant hardware will arrive at some point, organizations will integrate it when it does, and until then there is nothing practical to do. That framing is both inaccurate and increasingly costly to believe. We are not in a &#8220;wait for quantum&#8221; era. We are in a &#8220;prepare for quantum&#8221; era, and preparation is an active, infrastructure-intensive undertaking. Organizations that treat it as passive will find themselves starting from scratch when quantum utility arrives. Those who build now will be able to absorb it. The distinction matters most in the life sciences, where the cost of falling behind can be measured in years of delayed discovery for diseases that are not adequately served by today&#8217;s therapeutics. This is not a problem exclusive to drug discovery; it also

Quantum computers today are fragile: they lose their quantum state to noise and decoherence faster than a useful algorithm completes. Quantum error correction (QEC) makes longer computations possible by encoding each logical qubit across many physical qubits, so that errors can be detected and removed without disturbing the encoded information. In practice, QEC runs as a repeating cycle (see Fig. 1): in each round, the hardware measures a set of parity checks, called stabilizers, whose outcomes (the syndrome) reveal where errors have occurred without collapsing the logical state. A classical decoder then reads the syndrome, infers the most likely errors, and either records a correction to apply later or triggers a physical recovery. Figure 1 – The quantum error correction cycle. On the quantum hardware, (1) a logical qubit is stored across many physical qubits, and (2) each round of stabilizer (parity-check) measurements produces a syndrome. The syndrome passes to classical processing, where (3) a decoder infers the likely error and (4) issues a recovery command that is fed back to the hardware. The cycle repeats every round. The challenge is latency [1] (see our earlier post, A framework for quantum-classical integration decisions ). On today’s superconducting hardware, for instance, one round takes on the order of one microsecond. If the decoder cannot keep up with that rate, a processing backlog builds and stalls the computation. Popular decoders such as minimum-weight perfect matching (MWPM) [2], which infers the most likely errors by pairing up syndrome signals in a graph, grow more expensive as the quantum error-correcting code size gets larger. A pre-decoder eases this bottleneck with a fast first pass that clears the easy, high-confidence errors, leaving the full decoder a much smaller problem. This is where AI-based pre-decoders [3,4] come in, such as NVIDIA Ising Decoding . In this post we show how we trained NVIDIA Ising Decoding on AWS, how a range of ac

Abstract Claims of quantum advantage in machine learning often rest on classical comparators that lack the same features, on simulation alone, and on unreported hardware cost. QBioBench is a benchmark of quantum machine learning on peripheral biosignals that holds quantum and classical models to the same features and reports calibration and hardware cost. It comprises three clinical tasks, 12-lead ECG diagnosis (PTB-XL), single-lead apnea detection (Apnea-ECG), and wearable stress detection (WESAD), each reduced to six to eight shared dimensions. A factorial grid of projected and fidelity quantum kernels and variational classifiers is screened in noisy simulation, and the promoted configurations are evaluated in an exploratory study on an IBM Nighthawk r2 processor on the full test pools of 510 apnea minutes and 512 PTB-XL records. Every prediction is recovered from the device records, intervals resample recordings or patients, and classical baselines are trained on the same units and tested on the same executed inputs. No quantum model reaches its matched support vector machine in ROC-AUC on either primary task, and none is separably better in balanced accuracy. The angle-encoded fidelity and projected kernels reach ROC-AUC 0.697 and 0.693 on apnea, paired differences of $-0.127$ and $-0.119$ to the support vector machine, and both are classical by construction, since the entangling layer of the encoding cancels from the fidelity kernel and leaves closed-form local expectations in the projected kernel. A variational classifier comes closest, reaching 0.797 on apnea (difference $-0.012$, 95\% interval $[-0.052, +0.027]$), and falls to chance without its two-qubit gates. Test sets of the size that circuit budgets favour are unreliable, as random 80-minute subsets of the apnea pool give the fidelity kernel a central 95\% range of ROC-AUC from 0.589 to 0.797. Readout mitigation changed ROC-AUC by at most 0.015.

Abstract Non-Hermitian quantum dynamics lie in an intermediate regime between unitary Hamiltonian dynamics and trace-preserving non-unitary open quantum system dynamics. Given differences in the noise tolerance of unitary and non-unitary dynamics, it is interesting to consider implementing non-Hermitian dynamics on a noisy quantum computer. In this paper, we do so for a non-Hermitian Ising Floquet model whose many-body dynamics gives rise to persistent temporal oscillations, a form of time crystallinity. In the simplest two qubit case that we consider, there is an infinitely longlived periodic steady state at certain fine-tuned points. Using a generalized Floquet analysis, we show that infinitely long-lived oscillations are generically lost for arbitrarily weak values of common types of noise and compute the corresponding damping rate; this result is confirmed numerically using IBM's Qiskit platform. We further show that the complex gaps responsible for oscillation damping are opened generically at first order in perturbation theory for any convex combination of depolarization, relaxation, and dephasing, establishing that no engineered mixture of these noise channels can stabilize the time-crystalline phase. Experiments on a real device (ibmq-lima) are consistent with rapid oscillation damping, though a significant mismatch between the manufacturer noise model and observed device behavior complicates quantitative comparison, illustrating the importance of rigorous analytical noise analysis.

Abstract Tracking the dynamics of a quantum system is conventionally achieved by monitoring the system continuously in time and filtering the information contained in measurement records via the causal quantum trajectory approach. However, in practical scenarios, there is often loss of information to the environment, leading to filtered states that are impure because of decoherence. If real-time tracking is not required, the lost information can be maximally extracted via acausal quantum state smoothing , which has been theoretically proven to better restore the system’s coherence (purity) than causal filtering. Interestingly, quantum state smoothing requires assumptions about how any lost quantum information (unobserved by the experimenter) was turned into classical information by the environment. In this work, we experimentally demonstrate smoothing scenarios, using an optical parametric oscillator and introducing ‘observed’ and ‘unobserved’ channels by splitting the output beam into two independent homodyne detectors. We achieve improvement in state purification of 10.3% ± 1.6%, squeezing restoration of 7.6% ± 2.6%, and show that smoothed states are better estimates of hidden true states than those from conventional filtering. The estimation techniques used in this paper are promising for many applications in quantum information that incorporate post-processing.

We study a finite-width two-dimensional quantum ring with a quadratic $d$-wave altermagnetic term, Tan--Inkson confinement, a perpendicular magnetic field, and independently tunable Aharonov--Bohm (AB) flux. The altermagnetic interaction mixes $m$ and $m\pm2$ angular channels while preserving their parity. Circular symmetry renders the crystal orientation spectrally irrelevant and makes the two spin blocks exactly isospectral. The resulting same-parity anticrossings are resolved at low filling, and multichannel mixing is found near the Fermi level of highly occupied rings. Independent converged calculations for $N_e=1400$ and $1800$ establish the reconstructed Fermi edge and magnetic response in a finite field window and the persistent current over a full AB flux period. The analytic conventional reference separates radial-subband depopulation (dHvA-type cycles) from finer finite-ring shell oscillations; we do not assign a global Fourier spectrum to unverified altermagnetic field scans. The few-electron thermal response is obtained from an exact fixed-particle-number canonical partition function, avoiding finite-system errors of a fixed-mean-number approximation. The circular model supports an equilibrium charge current but no persistent spin current.

Problem structure is regarded as a key factor influencing the performance of the Quantum Approximate Optimization Algorithm (QAOA), yet it remains an informal notion without a precise mathematical characterization. In this work, we address this issue by identifying a mathematical object that captures problem structure as seen from the perspective of the target state amplitude in single-layer QAOA. Specifically, we show that this structure is encoded in a joint probability distribution induced by the unique coarsest partition of the computational basis, determined by problem cost values and mixer-dependent walk counts. The statistical dependence between these classes provides a means of quantifying the available problem structure and identifying necessary conditions for exponential amplification. To assess the extent to which this structure can translate into algorithmic performance, we establish a mean-max non-separation bound relating the parameter-averaged probability of measuring the target configuration to its variational maximum. For NPO-PB problems with polynomially many distinct mixer eigenvalues, these probabilities exhibit the same scaling up to polynomial factors. This allows us to characterize the exponential scaling of optimal amplitude amplification by analyzing the parameter-averaged probability without explicitly optimizing the variational parameters. We then derive an exact expression for the parameter-averaged probability as a matrix inner product involving two objects that separately encode the joint structural distribution and the mixer dynamics. This representation provides a framework for identifying the structural mechanisms governing the amplification of the target-state probability or its exponential suppression relative to the mixer capacity. We demonstrate these mechanisms through analytically tractable examples involving transverse field and Grover mixers.

We review what it means for a relativistic particle to be localized and argue that the most useful approach is through local measurement. This perspective ties localization directly to relativistic causality and measurable outcomes in spacetime. Strict localization in quantum field theory is formalized by states that give the same expectation value as vacuum for all local observables outside some spacetime region. With this formalism, single photons cannot be strictly localized, but coherent states can. The structure and interpretation of local observables and local operator algebras are discussed in connection with the Reeh-Schlieder theorem. Since probabilities of local measurement outcomes cannot vanish in vacuum, particle detection events must be phrased carefully. Key characteristics of strictly localized states are surveyed alongside concrete strategies for constructing them. The relationship between localization, causality, and on-demand sources is analyzed, finding that strictly localized states can represent localized, propagating information in quantum field theory. Explicit examples of localized photonic states are presented with an emphasis on quantum optics, including states that approximate single photons and (entangled) Bell states.

We propose distributed dual-comb spectroscopy, a quantum-enhanced sensing architecture that simultaneously exploits spatial- and spectral-domain entanglement to improve the extraction of global spectroscopic information across broadband frequency ranges. Our scheme consists of a network of Mach-Zehnder interferometers interrogating spatially separated samples, each driven by a classical frequency comb at the bright port. A single two-mode squeezed frequency comb is distributed through a passive beam-splitter array into $K$ entangled combs, establishing multipartite correlations across sensors while preserving intrinsic spectral entanglement. The protocol is compatible with both heterodyne detection and division detection, and enables parallel estimation of weighted-average absorption features over multiple frequency components. Compared with spatially separable quantum strategies requiring $K$ independently engineered nonclassical comb sources, our approach achieves enhanced signal-to-noise performance using only a single quantum resource distributed across the network. These results establish a scalable route toward broadband distributed quantum spectroscopy with simultaneous spatial and spectral advantage.

Coherence preservation and environmental renewal offer competing ways of controlling quantum memory and transport. We show that a seemingly natural protocol which exactly replaces the bath occupations while preserving arbitrary system--bath coherences need not correspond to a physical fermionic state. We instead construct a two-reservoir protocol with independent, number-conserving thermal attenuators, for which complete positivity and fermionic admissibility hold by construction. Physical attenuation necessarily modifies bath populations as well as cross correlations; the coherence control is not an independent hard-reset knob. Quadratic dynamics reduces the stroboscopic problem to an exact matrix fixed-point equation without a weak-coupling or Markov approximation. Analytically, coherence retention enhances the leading short-cycle transfer rate, including the complete-erasure limit; no general endpoint-vanishing theorem exists. An exact stationary continuity theorem forces the through-current to vanish whenever either reservoir is left entirely unrefreshed, although no analogous theorem suppresses it at complete erasure. For biased structured reservoirs, exact finite-chain calculations display distinct coherence-, current-, and signed energy-transfer operating points; a resolved high-retention boundary layer exposes strong finite-size sensitivity of the coherence peak. The model provides a microscopic, fermion-admissible benchmark for the interplay of reservoir coherence, particle transport, and energetic exchange.

Group IV color centers in diamond -- silicon, germanium, tin, and lead-vacancy centers -- are a promising platform for quantum networking. Typical Group-IV creation utilizes ion implantation during diamond growth that leaves the color centers with a broad depth distribution and damage-induced strain inhomogeneity. Deterministic placement and damage reduction in Group IV generation are essential for improving this platform. In this letter, we report on the localization of germanium-vacancy (GeV$^-$) to a $<$ 10 nm layer via the timed injection of GeH$_4$ during microwave plasma chemical vapor deposition. In this layer we have realized 17 ppm of Ge and a strain-free environment for the GeV$^-$. Subsequent electron irradiation and annealing have generated a sheet density of 0.12 GeV$^-$/$μ$m$^2$. The minimal damage from color center generation mitigates spectral inhomogeneity and allows spectral resolution of isotopic clusters, with the best cluster having an inhomogeneous distribution of 2.14 GHz and an average linewidth of $47 \pm 11$ MHz. Our study gives insight into formation dynamics of GeV$^-$ in delta-doped systems and estimates our vacancy to GeV$^-$ yield to be $\geq$ 90%, establishing an athermal nearest-neighbor formation model. We further characterized the spin $T_2^*$ and set a lower bound of 730 ns, limited by a paramagnetic defect.

The two-dimensional Hubbard model was originally proposed as the minimal model of uniform $d$-wave superconductivity in the cuprate high-temperature superconductors, but recent calculations with relevant parameters in a realistic doping regime have often found other ground states. Further, uncertainty remains over such results due to the intrinsic bias of different computational methods. Here we address this uncertainty through state-of-the-art neural tensor network and neural backflow state simulations, enabled by large-scale GPU computation, that together reach an unprecedented variational accuracy on lattices with up to 1024 sites. At $1/8$ doping in the pure Hubbard model, as well as with next-nearest-neighbor hopping relevant to the hole-doped cuprates, we reveal a near degeneracy among a low-energy uniform $d$-wave state, superconducting stripes, and non-superconducting stripe states on the milli-$t$ energy scale. Our work rebalances the narrative that the Hubbard model supports a single dominant order in relevant parameter regimes towards a picture of extreme competition between stripes and superconductivity.

Pauli-based computation (PBC) is a measurement-based model of quantum computation that samples from output distributions of universal Clifford+$T$ circuits. Here, we provide a normal form (NF) that completely characterizes its adaptive and entanglement structures. These insights unify PBC with one-way quantum computing as dual or `time-reversed' counterparts. We use the NF to advance strategies for distributed computation and investigate magic-state injection rates. We also demonstrate an exponential improvement in the detection of unnecessary magic-state qubits, allowing their efficient removal. Our NF further enables ahead-of-time circuit compilation using PBC, reducing CNOT gate count and quantum memory of random quantum circuits on average by 50% and 40%, respectively, beating other state-of-the-art compilers.

Belief Propagation combined with Ordered Statistics Decoding (BP OSD) is an open-source decoding tool used widely within the community due to its versatility and ease of application to Quantum Low Density Parity Check (QLDPC) codes. However, the degeneracy of quantum codes has been observed to degrade the performance of BP OSD, particularly leading to error floors for low physical error rates. Here, we investigate the low-weight error configurations responsible for such failures in Bivariate Bicycle codes. We show that, at code capacity, BP OSD fails on errors whose weight is significantly smaller than d/2, arising from global symmetries of the decoding graph that prevent the convergence of parallel BP. Furthermore, our analysis reveals new pitfalls that can arise when analysing the performance of BP OSD in the rare events regime, such as loss of ergodicity in splitting methods and numerical instabilities in the decoder. We show how to mitigate these failure mechanisms by modifying the BP update rules and the decoder implementation, leading to substantial improvement in logical error rate.

The promise of efficiently solving classical optimisation problems on quantum computers is tantalizing. As many such problems can be mapped to approximating the ground state of spin-glasses, paradigmatic models for studying many-body localisation, it is natural to ask if some of the intuition coming from quantum statistical mechanics can help guide the construction of novel quantum optimisation algorithms. In this work, we discuss how continuous reverse quantum annealing crossing a many-body localisation transition can be accelerated by considering the density of Landau-Zener crossings as the system is quenched. We provide an interpretation of this behaviour in terms of an effective Fokker-Planck equation for the success probability of the algorithm. This interpretation suggests an improvement in the required annealing time as a function of the system size $N$, which goes from $\mathcal{O}({\rm poly}(N))$ to $\mathcal{O}(1)$ for reference states with non-vanishing energy density. We show that the continuous dynamics can be Trotterised with a number of steps that remains modest as system size increases, making it appealing for near-term devices. For the resulting circuit implementation, we provide a quantitative strategy for determining the parameters of the time-dependent Hamiltonian. We compare the performance of our digitised algorithm, which we call FRIO, against that of the QAOA for finding the ground state of spin-glass problems, in particular the SK model. The numerical results suggest that with suitably selected circuit parameters which can be efficiently found using thermalizing dynamics, FRIO almost always outperforms the conventional QAOA ansatz with pre-optimized angles.

We consider the discrimination of two quantum channels acting on bosonic modes, with a probe state of fixed mean photon number and no ancilla. We prove that pure probes are optimal: for every mixed probe there is a pure probe with exactly the same mean photon number that performs at least as well. The result holds for arbitrary channels and for every figure of merit built from the Chernoff quantities $\Tr[ρ_1^sρ_2^{1-s}]$, including the quantum Chernoff exponent, as well as for the single-shot error probability. The proof relies on a decomposition of any state of mean photon number $\nb$ into pure states of mean photon number exactly $\nb$, which extends a matrix rank-one decomposition of Huang and Zhang to density operators of infinite rank.

Fault-tolerant syndrome extraction is fundamental to stabilizer-code-based quantum error correction, yet existing general protocols incur substantial costs in either circuit depth or width. In this work, we design ancilla stabilizer states for a general transversal circuit to construct a family of fault-tolerant syndrome-extraction gadgets that interpolate between Shor and Steane syndrome extraction for any stabilizer code. The result is a configurable trade-off between circuit depth and width.

We study variational preparation of ground states and sector-resolved excited states in the $(1+1)$-dimensional lattice Gross-Neveu model. We construct fixed circuits preserving either total fermion number or every flavor number, and a problem-specific scalable-circuit adaptive variational quantum eigensolver (SC-ADAPT-VQE). Classical circuit benchmarks cover massless and massive systems through 30 qubits, using exact-diagonalization and tensor-network reference results. Imposing flavor-number conservation improves the achieved energies in the completed two-flavor comparisons. Selected massive fixed-ansatz benchmarks with one to four flavors have relative energy errors of approximately $1 \times 10^{-5}$ - $2 \times 10^{-4}$, smaller than the quoted literature errors where available, although discretizations and computational resources differ. The adaptive pool combines translated bulk and boundary-sensitive generators with an interaction-sensitive cross-flavor family. Selected massive SC-ADAPT benchmarks with one to three flavors have relative energy errors below $2.1 \times 10^{-3}$. For one flavor, matrix-product-state evaluations extend the transferred circuits to 60-400 qubits without target-side operator selection or parameter optimization, giving energy deviations of approximately $0.35\%$ - $1.76\%$ from density-matrix renormalization-group reference values at maximum bond dimension 256. At fixed flavor number, range caps, and append count, the adaptive construction has a precompilation local-factor count linear in volume and a volume-independent shared-parameter count; fixed-accuracy performance at arbitrary volumes remains unestablished. Sequential deflation also prepares low-lying states within a fixed flavor-number sector, with projector fidelities providing a basis-independent assessment of degenerate target eigenspaces.

Discrete time crystals exhibit robust subharmonic oscillations, spontaneously breaking the discrete time-translation symmetry of a periodic drive. Since their emergence, the question of whether other types of temporal many-body order can exist has attracted considerable attention. Here we identify discrete time liquids -- a new form of spatiotemporal order characterized by short-range temporal coherence as a result of time-solitons. We study a two-dimensional spin system coupled to a finite-temperature cavity, whose fluctuations provide a noisy, approximately periodic drive with only finite temporal coherence. Remarkably, the spins nevertheless form a metastable state with robust period-doubled dynamics over an extended parameter regime. Unlike a time crystal, this state has only finite temporal coherence: individual trajectories stochastically switch between the two symmetry-related temporal configurations of the period-doubled response. We identify these switches as time-solitons: topological defects in temporal order that preserve local period doubling while destroying long-range temporal coherence, thereby producing the time liquid state. We propose a minimal model which reproduces the distribution of temporal correlations of the many-body system, suggesting a general description of the time liquid as a time crystal with a finite density of time-solitons. Because these solitons can occur at arbitrary times, ensemble averaging restores continuous time-translation symmetry, raising the intriguing possibility that discrete time liquids can exist in thermal equilibrium.

Numerically simulating quantum many-body systems is one of the central challenges in modern physics, as the exponential growth of the Hilbert space with system size renders large-scale exact solutions intractable. Over the past decade, generative artificial neural networks have emerged as powerful wave function ansätze that have powered advances in finding ground state representations, reconstructing quantum states from data, and modeling dynamics in quantum many-body systems. While recurrent neural networks (RNNs) are computationally efficient, the recurrent nature can limit their capacity to capture long-range correlations. Transformer models with their underlying self-attention mechanism excel at capturing these long-range correlations, but incur increased computational requirements, restricting applications to small physical systems. In this work, we address these limitations by exploring the multi-layer perceptron (MLP) mixer model as a wave function ansatz. By mixing information globally and locally through the system via a computationally lightweight mixing strategy, this architecture promises to combine the ability to capture long-range correlations with low computational costs. We benchmark the model on finding ground state representations of two-dimensional quantum many-body systems in various phases of matter and investigate the behavior of representational accuracy and computational efficiency for different physical system sizes. By comparing its performance to RNNs and transformer models with single-site and patched input definitions, we demonstrate that the MLP mixer architecture performs competitively with state-of-the-art network models. We further show that a hierarchical combination of this model with the transformer model outperforms other state-of-the-art architectures for large-scale quantum systems, opening new avenues for investigating quantum phases of matter.

Field-theoretic analysis has predicted that the edge of a double quantum spin Hall insulator (DQSHI) can undergo an interaction-driven transition from a phase with fermionic edge modes into one with only bosonic modes. All single-fermion edge excitations are gapped in this bosonic edge phase, but fermion pairs remain gapless, leading to distinct experimental signatures. We numerically simulate the interacting DQSHI edge and verify the existence of the bosonic edge phase. This calculation requires an explicit bulk embedding of the DQSHI edge, due to its mixed anomaly between charge and $S^z$ conservation. We hence employ segment DMRG on an infinite two-dimensional cylinder, where the DQSHI bulk is modeled in terms of two copies of the spin-up lowest Landau level, combined with their time-reversed counterparts. We find that interactions can open a single-fermion gap at the DQSHI edge while fermion pairs remain gapless, matching the predictions for the bosonic edge phase. We find the scaling of the single-fermion gap with interaction strength to be consistent with field-theoretic calculations, and discuss the relevance of the bosonic edge phase to twisted homobilayers of WSe$_2$ and MoTe$_2$. We elaborate on the methodological extension of the segment geometry used here to other topological phases with edge anomalies.

We provide a fully quantum-mechanical description of the continuous measurement of wavelike dark matter. Our focus is cavity haloscopes, although our results inform a broad range of axion searches. We extend the input-output formalism by treating the axion as a quantum field, finding how its quantum state is imprinted onto higher-order moments of observables of the outgoing transmission-line modes. We further develop a novel measurement-record formalism, which computes the joint probability distribution of all measurement outcomes and is well suited to studying the axion in the time domain. With it, we compute the exact axion-induced number distribution for the first time, demonstrating that it is not Poisson. We argue that virialized axion dark matter is expected to be in a Gaussian quantum state, and show that number or quadrature measurements can distinguish this from the predictions of a coherent state or even a Bose-Einstein condensate. Finally, we show that intrinsically quantum effects, such as those from Fock or squeezed axion states, are far too weak to detect.

AI agents are increasingly capable of constructing quantum algorithms and proofs, yet machine-checked proofs alone cannot guarantee that the intended problem is solved or that resource claims match the verified computation.Here we introduce Lean-QuantumAlg, a Lean 4 framework for trustworthy AI-assisted development of quantum algorithms.Its Algorithm-Solves-Problem contract binds correctness, success probability, borrowed-state restoration and quantum and classical resource bounds to a single execution, while separating the guarantees that Lean checks from the problem specifications and execution models that humans review. We demonstrate the framework on nine AI-formalized quantum algorithms, from Grover search to quantum attacks on RSA-2048 and P-256, with less than 1% of each algorithm's imported source code requiring statement-level human review once the shared framework has been audited. By integrating reusable mathematical foundations, certified algorithmic primitives and execution-grounded verification, Lean-QuantumAlg provides a basis for AI agents to construct and certify quantum algorithms, opening a path toward scalable AI-driven discovery of quantum algorithms.

Mechanical vibrations are fundamental to a wide range of physical phenomena and technologies, yet their ability to actively shape free-electron dynamics remains largely unexplored. Here we theoretically show how an optomechanical membrane provides a phonon-assisted optical interface for controlling free-electron recoil and sensing localized forces. Transverse membrane motion scatters cavity light into high-momentum evanescent sidebands that enable phase-matched interaction with electrons traveling in vacuum. Beyond supplying momentum for phase matching, the vibration amplitude controls the electron-light interaction strength and redistributes electron populations among recoil orders. External forces that perturb the vibration are thereby encoded in the electron recoil spectrum. Under the modeled conditions, electron readout of localized stochastic forces can yield a higher signal-to-noise ratio than a Gaussian optical homodyne benchmark at equal detected probe rates. These results provide a theoretical basis for mechanically reconfigurable free-electron optics and mode-selective mechanical sensing.

A two-level emitter chirally coupled to a waveguide imprints a $π$ conditional phase on a two-photon pulse, a key component assumed in quantum photonic neural network architectures, but whether it survives the pure dephasing of a solid-state emitter is unknown, since no two-photon scattering treatment includes it. We derive the dephased two-photon amplitude in closed form and validate it against an independent Fock-state master equation. The conditional phase is pinned at exactly $π$ at every dephasing rate examined: dephasing destroys the amplitude carrying the nonlinear phase rather than rotating it. The one- and two-photon channels are not attenuated equally, so dephasing does not simply scale the node down but reweights it between photon-number sectors---an error no phase setting can train away. The standard factorization of two-photon correlators, exact for arbitrary loss, fails at first order in $γ_φ$, discarding $16$--$81\%$ of pairs over $γ_φ/γ=0.1$--$1$.

We prove a conjecture of Yu, Lai, and Oh: their rounded family of strengthened quantum Hamming bounds, which interpolates between Hamming-type bounds and the Singleton bound, holds for arbitrary exact quantum subspaces of dimension $K>1$. The result covers every integer local dimension $p\ge2$, every integer $t\ge1$, both distances $2t+1$ and $2t+2$, and every interpolation parameter $e\in\{0,\ldots,t\}$. Yu, Lai, and Oh proved these bounds for pure codes and for general codes of distance three or four; the case $e=0$ contains the ordinary quantum Hamming bound for general codes, recently proved by Zhang and Chen. More generally, for $p\ge3$, we prove the inequality $Kf(0)\le p^n\mathbb{E}f(X)$, where $X\sim\operatorname{Bin}(n,1-p^{-2})$, for every real polynomial $f$ of degree at most $D$, with $2\le D<d$, that is nonnegative on $\{0,\ldots,n\}$ and positive at zero; here $n$ and $d$ are the code length and distance.

We propose a quantum architecture that achieves addressable and parallel universal fault-tolerant logical in high-rate codes. The codes are obtained from the flexible concatenation of small-distance high-rate self-dual CSS codes. Addressable and parallel universal logic on the resulting $K$ logical qubits is injected by fault-tolerantly preparing and then consuming diverse logical $K$-qubit CSS stabilizer states and logical $\lvert H \rangle^{\otimes K}$ global magic states. Flag-at-origin is used to prepare the stabilizer resource states while a concatenated cultivation protocol prepares the global magic states. These resource states are consumed by Steane-QEC or Knill-QEC teleportation gadgets, which simultaneously perform quantum error correction. Any quantum algorithm with $T$-depth $D_T$ can be executed by consuming $12D_T$ or fewer resource states. We benchmark the fault-tolerant preparation of the resource states for several two-level concatenations of the $[[k+4,k,2]]$ H codes and the Hamming $[[15,7,3]]$ code. In particular, we find that the concatenated cultivation offers at least one order of magnitude spacetime reduction compared to cultivation in the surface code.

We propose an operational resolution of the FLRW big bang singularity using quantum probes satisfying a curvature coupled Klein-Gordon equation. Applying the Madelung-Bohm decomposition of a Klein-Gordon field on a classical near-singularity FLRW background, we show that the induced conformal geometry renders curvature invariants finite and makes past directed causal geodesics complete. The classical big bang surface is therefore inaccessible to this class of quantum probes in finite effective proper time, while the underlying FLRW spacetime remains singular.

We introduce a random sampling method for testing the weak Eigenstate Thermalization Hypothesis (wETH) that is particularly useful for large, sparse Hamiltonians. We test the method on a well-studied Rydberg atom system that exhibits both two- and three-body dipole-dipole interactions. Our results show that our method allows for the study of system sizes significantly beyond the limits of exact diagonalization. We find that the fluctuations in eigenstate expectation values decay as the Hilbert space dimension $D^{-1/2}$, consistent with wETH and in agreement with previous numerical results.

A recent work considered the Page curve for entanglement entropy of a freely expanding one-dimensional Fermi gas starting from a finite box (the system) in a zero-temperature initial state that then expands in to a semi-infinite vacuum (the environment). For the case with a single defect at the system-environment junction, it was shown that the Yang-Yang entropy of the system computed from semiclassical hydrodynamics agrees with the microscopically computed entanglement entropy, yielding the Page curve. On the other hand, the environment Yang-Yang entropy showed a monotonic increase. Here, we propose a hydrodynamic description to obtain the eigenvalues of the microscopic correlation matrix for a nonzero temperature freely-expanding Fermi gas. For the system, the phase space density directly gives the correlation matrix eigenvalues and thus, via the Yang-Yang formula, yields the von-Neumann entropy. For the reservoir, a modification of the phase space density is required in the Yang-Yang formula, to incorporate coherences, in order to reproduce accurately the entropy. The hydrodynamic description of correlation matrix eigenvalues also leads to a Levitov-Lesovik type formula for the full-counting-statistics for a finite system in the transient regime. We provide a heuristic derivation of the correlation matrix eigenvalues based on a semiclassical wave-packet picture.

Fault-tolerant quantum computing requires quantum gates that combine short duration, high fidelity, and robustness to noise. As quantum processors scale, robustness becomes increasingly important because exhaustive characterization and frequent recalibration of individual gates become impractical. We present a comprehensive optimal-control framework for controlled-Z (CZ) gates between directly coupled, frequency-tunable transmons that systematically accounts for intrinsic Hamiltonian errors and realistic decoherence mechanisms, including energy relaxation and dephasing. Using smooth, single-shot flux pulses, we obtain 12-ns CZ gates---close to the theoretical speed limit of 11.6 ns---with intrinsic errors suppressed to the $2\times10^{-5}$ level. We construct dephasing noise models, calibrated against published experimental measurements, that capture fast dephasing from room-temperature control electronics and slow dephasing from $1/f$ flux noise. Using these models, we identify dephasing sweet spots that suppress sensitivity to dephasing noise. We further exploit transmon asymmetry as a design parameter to access distinct noise-resilient operating regimes. These results establish an experimentally applicable framework for balancing gate speed, fidelity, and noise robustness while reducing characterization and recalibration overhead.

We prove that the randomized communication complexity of Vector-in-Subspace in $\mathbb R^n$ with error at most $1/3$ is $Θ(\sqrt n)$. Alice holds a unit vector $u$ and Bob holds an $n/2$-dimensional subspace $H$; they must distinguish $u\in H$ from $u\in H^\perp$. An exact one-way quantum protocol uses $O(\log n)$ qubits, making the problem a geometric example of an exponential quantum advantage over interactive classical communication. Our lower bound matches Raz's $O(\sqrt n)$ upper bound, improves the $Ω(n^{1/3})$ lower bound of Klartag and Regev, and removes the total-rank restriction in Grupel's $Ω(\sqrt n)$ result. The proof establishes a Gaussian moment bound over complete rectangle partitions. A complex Gaussian representation yields a vanishing even moment whose cancellation is preserved when averaging over the partition. We control the signed conditional moments around a real center by decomposing conditional Gaussian measures into fixed coordinates and sub-Gaussian components. Combining this estimate with spherical harmonic analysis gives the communication lower bound.

Majorana drew a symmetric multiqubit state as points on the Bloch sphere, antipodal to the zeros of its overlap with spin coherent states. Projecting only one qubit of a general state leaves the others in a state that varies with direction. Its entanglement invariants are eigenvalues of a non-Hermitian matrix and form bands over the sphere. Exceptional points appear, without gain or loss, where the entanglement family of the rest changes. Circling one exchanges two bands, so the bands form one Riemann surface. At five qubits it fixes the entanglement class up to finitely many choices.

I discuss two important quantum optics experiments which depend on two particle interference. In the years since their first demonstration many interesting and instructive variants have appeared, including the use of atoms instead of photons as the interfering particles. This chapter gives a pedagogical overview of some of these results and argues that the two effects are closely related.

Modular quantum architecture requires long-distance quantum interconnects to stitch together individual processor modules. Such interconnects, long-distance couplers or L-couplers, must support coherent quantum operation over meter-scale distances and scale to multiple connections between any two modules. Here we demonstrate four L-couplers operating between two 120-qubit IBM Nighthawk R1 superconducting qubit processors. Each L-coupler joins two Nighthawk lattice qubits through two frequency-tunable L-qubits, two RF-SQUID based "i2m" couplers, and 80 cm of superconducting aluminum coax. Each cable installs perpendicular to the processor surface, to enable denser connections, and is joined to the chip by an indium-to-indium room temperature pressure bond made after both modules were mounted. L-coupler modes near 5 GHz, with internal quality factors of 0.86 to 1.09e6, carry relay-based state transfer at a mean network benchmarking fidelity of 99.00%, with a best link of 99.29 +/- 0.07%. We then realize distant CZ gates between lattice qubits in separate modules at a mean fidelity of 94.75%, with a best link of 96.42 +/- 0.28%, and use them to generate entangled states across the two processors, including a demonstration of simultaneous Bell pair generation using two adjacent L-couplers. These four high-fidelity L-couplers establish a practical path to scalable quantum interconnects for modular quantum computing.

Two single-ion optical clocks, located in the United Kingdom and in Germany, are compared remotely via a 2220\,km long optical fiber link. Both clocks are based on the ${}^2S_{1/2} (F=0)\leftrightarrow {}^2F_{7/2} (F=3)$ electric octupole (E3) transition in $^{171}\text{Yb}^+$. Using more than $10^6$ seconds of measurement data, we determine a fractional frequency difference of $1.0(4.8)\times 10^{-18}$, demonstrating agreement of the independently developed systems. To our knowledge, this constitutes the first international clock comparison reaching a fractional uncertainty below $5\times 10^{-18}$, an important milestone towards an anticipated optical redefinition of the SI second. The measurement uncertainty is dominated by that of the relativistic redshift correction between the two sites, which includes time-varying gravity potential differences. We exploit the large baseline between the two clocks to search for violations of Lorentz invariance. In the absence of statistically significant modulations, we improve constraints on the Robertson-Mansouri-Sexl parameter $α$ by approximately a factor of five in the uncertainty, and provide limits on corresponding parameters within the Standard-Model Extension framework.

We establish that transversal diagonal gates on exact qubit codes of distance at least two can be exhaustively classified within a finite search space. Although code-preserving physical gates can have continuous phases, any projective logical action induced by a transversal diagonal gate can always be realized by a physical gate of finite order. Crucially, we prove that this physical order has an upper bound determined solely by the code parameters. This order bound enables the subset-sum-linear-programming (SSLP) framework introduced in arXiv:2504.20847 to exhaustively enumerate all candidate discrete symmetries, after which the Knill-Laflamme equations determine the remaining continuous code parameters. Applying this method to the nontrivial diagonal sector of exact $((6,2,3))$ codes, SSLP yields $66$ candidate symmetry classes, of which exactly $15$ are realizable, supporting full projective diagonal logical cyclic groups of orders $2$, $3$, and $5$. In particular, for order $5$, the code is unique up to local unitaries and qubit permutations, equivalent to the code constructed in arXiv:2504.20847. This code also attains the minimum length $n=6$ among exact $((n, 2, \ge 3))$ codes whose full projective transversal group cannot be conjugated into the projective Clifford group.

Variational Quantum Algorithms (VQAs) are promising approaches for solving combinatorial optimization problems on near-term quantum devices. However, the role played by quantum resources such as entanglement and coherence during the optimization process remains poorly understood. In this work, we investigate the evolution of these resources in two VQAs--the Quantum Approximate Optimization Algorithm (QAOA) and the Feedback-based Algorithm for Quantum Optimization (FALQON)--applied to the Minimum Vertex Cover problem. We employ a variational resource-quantification framework based on the Bures metric and Uhlmann's theorem, in which an auxiliary quantum circuit is optimized to identify the closest resource-free states. This approach allows us to quantify Bures entanglement and Bures coherence of the algorithmic states without requiring full quantum state tomography. For the considered problem instance, QAOA exhibits a pronounced accumulation of entanglement in its initial layers, followed by a progressive reduction as the algorithm converges toward the optimal solution. Its coherence likewise decreases overall with increasing circuit depth, although a finite residual value persists due to the degeneracy of the optimal-solution subspace. In contrast, FALQON exhibits a substantially lower entanglement peak, reached at larger circuit depth, followed by a decay as convergence proceeds. Its coherence decreases smoothly and monotonically together with the optimization error. These results reveal distinct quantum-resource trajectories associated with the two optimization strategies and illustrate how entanglement and coherence evolve as variational quantum states approach solutions of a classical combinatorial optimization problem.

Impedance matching is a crucial feature of an amplifier used to increase its instantaneous bandwidth and is typically achieved using static LC resonators. Here we show an approach to impedance matching in parametric amplifiers using arrays of unequal Josephson-junction-based elements (rf/dc SQUIDs, SNAILs, etc). The elements act either as small-footprint flux-tunable inductors forming an impedance-matching circuit, or 'active' amplifier elements which result in amplifier gain. We develop an analytical theory describing these systems, predicting a quasi-non-periodic amplifier frequency and gain modulation with applied flux and the broadening of gain bandwidths. We demonstrate this in devices using arrays of flux-focused SNAILs where flux biasing varies across the array. We find instantaneous bandwidths of 200 MHz with $>$17 dB of gain centred at $\sim$5.4 GHz in a device without a static impedance matcher. This broadening of amplifier bandwidth is stable with $>$100 MHz bandwidth at 17 dB gain across $>$1.2 GHz tunable bandwidth. Our analytical model captures flux dependence and qualitatively reproduces gain-bandwidths giving confidence in our understanding of these systems and allowing operational figures of merit to be optimised in future devices.

The superconducting diode effect requires the forward and reverse bias currents to differ, a scenario achieved via inversion and time-reversal symmetries broken together. The latter, and the more crucial one, is inevitably achieved by a magnetic field. Here, we show that a spatio-temporally driven chemical potential of the form, $μ_j(t)=μ+V\cos(ωt+\kd j)$, achieves both at once. Applied to a helical Shiba chain, the drive transmutes a traveling Peierls phase via generating an odd-in-momentum term, equivalent to an imaginary next-nearest-neighbour Haldane-like hopping in real space. Remarkably, the protocol is spin-blind, which renders the time-reversal breaking via a synthetic gauge flux rather than an effective Zeeman field. The rectification is odd in the drive wavevector, with exact zeros at $\kd=nπ$ and an analytical optimum at $\kd=2π/3$. It is however, even in the exchange coupling, $J$ and persists even at $J=0$. Furthermore, the rectification scales inversely with the pair-breaking gap, yielding approximately $50\%$ rectification in the topological phase and $10\%$ in the trivial phase. Symmetry breaking is thus drive-controlled, allowing it to be switched on, tuned, and reversed without an external magnetic field.

Teaching quantum mechanics at the secondary school level remains a major educational challenge. Traditional historical approaches often present the theory as a sequence of disconnected phenomena, requiring extensive prior knowledge of classical physics before students can appreciate the conceptual structure of quantum physics. In this work, we present the design, implementation, and evaluation of a curriculum based on the two state (qubit first) approach, in which the fundamental postulates of quantum mechanics are introduced through mathematically accessible two level systems and realized with light polarization. The curriculum integrates theoretical instruction, laboratory activities, a coherent progression grounded in the interactive simulations, and inquiry based learning into a coherent pathway that progresses from quantum states and superposition to entanglement and the experimental violation of Bell's inequalities. A distinctive feature of the project is the experimental realization of the violation of Bell's inequalities obtained in a newly established quantum optics laboratory in an Italian high school, where students performed, for the first time in Italy, an authentic Bell test using polarization-entangled photons. The same educational framework was adopted for in service teacher professional development courses. Learning outcomes were evaluated through mixed methods. Preliminary analysis indicates significant improvements in conceptual understanding, confidence in using mathematical formalism, and appreciation of the relationship between theory, experimentation, and the foundations of quantum mechanics. The proposed curriculum shows that two-state formalism and supported by real laboratory experiences enables secondary-school students to engage more meaningfully with both the conceptual foundations of quantum mechanics and their experimental verification.

In quantum mechanics, conservation laws are usually understood only statistically and only in the context of unitary evolution: during such evolution, if an observable commutes with the Hamiltonian, its expectation value and Born-rule probability distribution remain unchanged. Individual measurement outcomes, however, disrupt even this weak form of statistical conservation. Recently, though, it has been argued that a stronger, non-statistical form of conservation, valid at the level of individual measurement outcomes, can be recovered. The proposal relies on the claim that any superposition of eigenstates of a conserved quantity must ultimately be prepared relative to another physical system, which serves as the relevant reference frame and remains correlated with the system being prepared. On this enlarged description, the change observed in the measured system is claimed to be exactly compensated by an opposite change in the preparer, thereby restoring conservation at the level of individual measurement outcomes. We analyze this proposal and argue that it faces significant conceptual difficulties. We show that the proposed mechanism is not adequately justified and, moreover, does not establish conservation in individual measurement outcomes as claimed.

We show that the concept of particles and antiparticles is related to the Weyl-Heisenberg group $W\!H_3$. Its generators are the position operators $\hat x^a$, the momentum operators $\hat p_a$, and the central element $Q_{\sf{v}}$, which defines a subgroup U(1)$_{\sf v}$ of $W\!H_3$. We show that the wave functions have a charge relative to the group U(1)$_{\sf{v}}$ equal to either $q_+=1/\hbar$ (particle $ψ_+$) or $q_-=-1/\hbar$ (antiparticle $ψ_-$). We call these eigenvalues of the operator $Q_{\sf{v}}$ quantum charges: $Q_{\sf{v}}ψ_\pm^{}=q_\pm^{}ψ_\pm^{}$. The wave functions $ψ_+$ and $ψ_-$ belong to the Hilbert spaces $\mathcal{H}_+$ and $\mathcal{H}_-$, on which unitarily inequivalent representations $π_\hbar$ and $π_{-\hbar}$ of the Weyl-Heisenberg group $W\!H_3$ are defined. These representations are related to each other by the antilinear charge conjugation operator $\hat C$, which maps $\mathcal{H}_+, q_+$ to $\mathcal{H}_-, q_-$. Charges $q_\pm^{}$ are intrinsic characteristics of the wave functions $ψ_\pm^{}$, similar to spin and electric charge. The wave function possesses one of these charges, $q_+$ or $q_-$, prior to the specification of any equations. We show that negative probabilities/energies and the Klein paradox in Klein-Gordon and Dirac theories are consequences of the violation of U(1)$_{\sf v}$-invariance in these theories. Restoring this invariance separates particle and antiparticles and eliminates all paradoxes at the level of first-quantized relativistic theories.

Predicting molecular electronic structure using Quantum Computing approaches is a challenge in Computational Chemistry. Traditional Variational Quantum Eigensolvers (VQEs) are typically hindered by optimization challenges. The alternative Generative Quantum Eigensolver (GQE) mitigates this by reformulating ground-state search as discrete sequence generation, but its Transformer backbone suffers from quadratic computational complexity, bottlenecking scalability for larger molecules. To address this, we introduce the Mamba Quantum Eigensolver (Mamba-QE), which replaces the Transformer with a Selective State Space Model (SSM) to process operator sequences with linear $\mathcal{O}(L)$ complexity. Additionally, we integrate a distance-conditioned mechanism enabling the direct prediction of complete potential energy surfaces (PES). Evaluated on the $H_2$ molecule, Mamba-QE reproduces Full Configuration Interaction (FCI) reference energies well within chemical accuracy, achieving an energy error below $3\times10^{-6}$ Ha across 16 geometries with zero variational violations. Mamba-QE maintains high expressive power while establishing a robust, scalable foundation for quantum simulations of complex molecular systems.

We explore the space-time cost of encoding of a bosonic mode into a set of qubits via various encodings, and their resilience to noise. In particular, we compare the performance of the unary Fock state encoding, an unexplored encoding of Fock states into Dicke states (``Dicke'' encoding), and the binary quadrature encoding. We do so by considering a displacement as well as a simulation of a Dicke model, coupling a bosonic mode to a set of atoms represented as qubits. Using classical simulations, we assess the accuracy and optimized space-time costs in terms of number of qubits, circuit depth and CNOT count of a quantum simulation of the time dynamics using these encodings. Although our study is far from comprehensive, we find that the binary quadrature encoding is overall most favorable in terms of being very space-efficient and relatively time-efficient due to the use of the quantum Fourier transform. Our novel Dicke encoding leads to very shallow circuits, but pays in terms of using many more qubits. We probe the use of an H2-2 Quantinuum trapped-ion qubit device (56 qubits) for displacement and Dicke model simulation in the low boson-number regime, where we find that noise leads to visible deviations from ideal circuit dynamics.

Motional modes of trapped-ion crystals in Penning traps can now be cooled to near their ground states via electromagnetically induced transparency (EIT) cooling. Numerical simulations are valuable tools for interpreting EIT cooling results and optimizing experimental protocols, but existing molecular dynamics codes are limited to the simulation of Doppler cooling. In this work, we fill this gap by implementing a semiclassical model of EIT cooling in a novel MD code. By simultaneously evolving the ions' internal quantum states and classical motion, we are able to calculate the instantaneous EIT laser forces acting on the ions. We first validate our code by comparing the single-ion cooling rate to fully quantum simulation results. Next, we analyze cooling of the drumhead modes in planar ion crystals, quantifying the effects of planar ion motion and a finite laser beam width. Finally, we demonstrate efficient EIT cooling of the axial modes in 3D ellipsoidal crystals containing up to 500 ions. Such crystals are a promising platform for future quantum sensing experiments with enhanced sensitivity. We find that the mode spectra of 3D crystals can be engineered to enable sympathetic cooling of the low-frequency $\boldsymbol{E}\times\boldsymbol{B}$ modes. This numerical framework provides a powerful tool for modeling sub-Doppler cooling techniques and for optimizing future quantum sensing and quantum information experiments.

The same classical f-divergence admits inequivalent extensions to quantum states. The question is whether these extensions can be obtained from a common operational variational principle. Here we generalize Matsumoto's reverse-test optimization by introducing a reference prior state. More explicitly, we minimize the statistical distinguishability between a forward and a reverse prepare-and-measure process, related by retrodiction through the chosen reference and subject to prescribed quantum averages. Distinguishability is quantified by the classical f-divergence between their complete records. For faithful states in finite dimension, we prove that the same spectral implementation attains the minimum simultaneously for every operator-convex f. Varying the reference allows us to interpolate between standard and maximal quantum f-divergences of the prescribed states, passing through the geodesic family. More precisely, a flat reference yields the standard quantum f-divergences, thereby giving the Nussbaum-Szkoła distributions a variational characterization as optimal records. Choosing either prescribed state as reference recovers maximal quantum f-divergences and Matsumoto's reverse tests, while power references realize the geodesic interpolation. In the relative-entropy case, this gives the passage from Umegaki to Belavkin-Staszewski relative entropy by changing the prior for retrodiction.

Combining topological insulators with chiral magnetic multilayers offers the opportunity to greatly enhance the spin-orbit torque (SOT) driven manipulation of hosted spin textures, however this also exposes devices to the often poor temperature stability of the commonly used, Bi$_2$X$_3$-based (X is a chalcogenic element), topological insulator films. In this work we demonstrate through in-situ-annealing and polarised neutron reflectometry that the multilayer at a Bi$_2$Se$_3$ interface remains magnetically robust up to a temperature of 350 $^{\circ}$C: even as the Bi$_2$Se$_3$ epilayer structurally deteriorates. Through x-ray photoemission electron microscopy, an intermediate annealing temperature of $\sim$ 200 $^{\circ}$C was found to improve the domain ordering of the multilayer, allowing for field-induced skyrmion nucleation, all whilst sustaining minimal damage to the topological insulator

Quantum computing represents a fundamental shift in computation, promising to solve problems currently intractable for classical computers. However, misconceptions persist; quantum computers are not universally faster, nor do they replace classical systems. Current Noisy Intermediate-Scale Quantum (NISQ) devices face significant challenges, including decoherence, high error rates, and limited scalability. Additionally, leveraging quantum systems requires rethinking traditional computing principles, adopting different programming models, and addressing the complexities of integrating quantum and classical workflows, making their practical use in computer science both demanding and non-trivial. This article provides a system-level perspective on quantum computing for computer scientists, software engineers, and IT professionals, examining its current capabilities, key architectural and software challenges, and potential paths toward quantum advantage in real-world applications within hybrid quantum-classical environments.

The local distinguishability of five bipartite and tripartite orthogonal product states (OPSs) has been effectively resolved, while that of five quadripartite OPSs has not yet been effectively addressed. In this paper, we give the local distinguishability of five quadripartite OPSs, where any two of these five states are orthogonal on exactly one subsystem. Based on the vectors of the numbers of pairwise orthogonality relations, we classify different sets of five quadripartite OPSs into nine categories, which correspond to 371 distinct orthogonality graphs. We show that the sets of five quadripartite OPSs corresponding to 355 of the 371 cases can be perfectly distinguished by local operations and classical communication (LOCC), whereas the sets of five quadripartite OPSs for the remaining 16 cases cannot exactly distinguished by LOCC. Our results enrich the theory of nonlocality for sets of OPSs.

We apply a large Gaussian basis set of size up to $N = 500$ to calculate the all-order Wichmann-Kroll vacuum polarization correction in highly-charged ion. For a hydrogen-like system, this allows us to obtain an accurate correction value with a level of precision comparable to that of traditional methods. We demonstrate that values of effects that can be calculated as the difference between two quantities, such as the nuclear model correction, converge faster than the absolute value of the correction. We discuss the basis extrapolation methods and show their use in estimating the error due to incomplete convergence. Finally, we show an application of the Gaussian basis set to calculation of the vacuum polarization screening correction in lithium-like ions.

We propose a quantum-enhanced matter-wave interferometry protocol based on fractional-revival dynamics of a Bose-Einstein condensate in a ring, combined with a controlled interaction quench. Using the Truncated Wigner Approximation, we show that nonlinear evolution to the quarter revival generates modest spin squeezing of $-2.03\pm0.28\;$dB, which subsequently degrades under further nonlinear evolution. In contrast, starting from a non-interacting condensate, a controlled interaction quench applied after the initial quarter-revival beam-splitter operation generates substantially stronger spin squeezing of $-14.57\pm0.27\;$dB. We further show that phase control at $t=3T_r/8$ rotates the squeezed quadrature onto the phase-sensitive direction $\hat{J}_y$, producing a phase-squeezed state at $t=T_r/2$. The subsequent quarter-revival evolution converts this phase-squeezed state into a number-squeezed state, enabling population-difference readout. The resulting sequence provides a route to quantum-enhanced interferometry using the intrinsic fractional-revival dynamics of a ring together with controlled interaction and phase operations.

We consider a continuous-time quantum walk stroboscopically subjected to projective measurements on two distinct targets with sampling time period $τ$. We construct a general renewal framework for the first-detection amplitude at each target, from which we obtain the associated splitting probabilities. For Hamiltonians with reflection symmetry, we further show that each dual-target first-detection amplitude can be viewed as an interference effect between a pair of single-target first-detection amplitudes. This formulation yields exact expressions for the splitting probabilities and gives special sampling times at which they undergo pointwise discontinuous jumps due to a form of ergodicity breaking associated with dark states. As an illustrative example, we apply the framework to a one-dimensional tight-binding lattice chain with nearest-neighbor hopping, and study the splitting probabilities as functions of the initial position and sampling time. Below a critical sampling time, $0<τ< τ_c$ where $τ_c = 2 π/ ΔE$ with $ΔE$ being the energy bandwidth, the splitting probabilities for large system sizes become equal to $1/2$, independent of the initial position, as long as this position does not coincide with target sites. Above the critical sampling time, $τ\geq τ_c$, the splitting probabilities deviate from $1/2$ and develop oscillations as a function of initial position. The wavenumber associated with these oscillations is $Q=2\sin^{-1}(rτ_c/τ)$, where $r$ is a positive integer. We also explore the effects of relative phase and spatial separation between different components of a coherent initial state on the splitting probabilities. Finally, we study how a finite number of measurements modifies the splitting probabilities and broadens the resonances at special sampling times.

We describe a compact and simplified experimental setup for the production of ultracold strontium atoms. Thanks to its low-power oven and coil-free Zeeman slower design, the vacuum system has an overall length of only 40cm including oven, Zeeman slower and all-glass science cell. The oven has a power consumption of 14W at 460°C and produces a collimated flux of 3 10^10at/(s cm^2) at this temperature. The laser system employs master-slave laser architecture throughout and requires neither second-harmonic generation nor tapered amplifiers, reducing cost and complexity. The system has been in continuous use for more than a year.

Electron--electron interactions can reconstruct Bloch wave functions, changing their geometry and the associated thermoelectric response. We derive the linear thermoelectric response within the Hartree--Fock (HF) approximation using the thermal length-gauge density-matrix approach, resolving Drude, symmetric quantum-metric, and antisymmetric Berry-curvature contributions. In a noninteracting Bloch eigenbasis, we separate the reconstructed Berry connection into the noninteracting connection and an interaction connection. This gives bare, coherence, and interaction-connection contributions to the anomalous thermoelectric response. We determine the constraints imposed by spatial inversion, rotational, time-reversal, and combined symmetries on the three transport channels. In the relaxation-time approximation, the leading weak-broadening behavior is $Γ^{-1}$ for the Drude contribution, $Γ$ for the quantum-metric contribution, and $Γ^0$ for the Berry-curvature contribution. The interband scalings apply away from band degeneracies. Self-consistent calculations for the triangular-lattice extended Hubbard model illustrate how interactions generate Berry curvature and a quantum metric, change the symmetry of the system, and thereby contribute to transverse thermoelectric transport.

Nanoscale nonreciprocal elements are needed to control signal flow in scalable quantum technologies, but existing nonreciprocal components are often bulky. Here, we show that a strongly nonreciprocal current-voltage relation can arise entirely from coherent elastic scattering in a mesoscopic Rashba nanowire with gate-defined scatterers. We first identify the symmetry constraints that enforce reciprocal transmission in a phase coherent conductor even when inversion and time-reversal symmetry are broken. We then show how gates that are capacitively coupled to the leads, together with a magnetic scatterer or transverse subband mixing, can remove these constraints. In the weak-scattering regime, nonreciprocal conductance originates from interference between distinct backscattering paths. In the strong-scattering regime, nonreciprocity can be resonantly enhanced by the hybridization of the transmitting channel with bound states that arise from a higher transverse subband or spin-split band. In this regime, we find that a bias-induced change in the gate potentials of about one percent can produce an order-unity diode response, i.e., electrons are transmitted almost as in a clean wire for one bias polarity, whereas for the other polarity the current is strongly suppressed.

We construct short triorthogonal codes for qudits of odd prime dimension by generalizing doubling, which combines a triorthogonal code with a code admitting a transversal phase gate, and raises the distance by up to two. This gives codes with parameters $[[28,1,4]]_3$, $[[37,1,5]]_3$, $[[72,1,6]]_3$, $[[118,1,8]]_3$, $[[33,1,5]]_5$ and $[[20,1,4]]_7$, each shorter than the cyclic, concatenated and Reed-Muller codes of the same distance, and a doubling construction of the $[[15,1,3]]_3$ code. When the columns of a generator matrix are regarded as charged points, triorthogonality becomes the vanishing of multipole moments up to octupole order, and doubling becomes a double layer of opposite charges; this picture explains why inputs with nontrivial coefficients can give shorter codes. We also show by exhaustive search that the shortest codes of distance three have length $11$ for $p=5$ and length $7$ for $p=7$. Combined with high-rate distance-two codes, the new codes reduce the cost of qutrit magic state distillation by up to an order of magnitude in regimes with high input noise.

A recent formulation of quantum belief showed that quantum retrodiction depends not only on the reduced density operator of the system of interest, but also on correlations with a hidden reference system, which leads to the notion of quantum belief equivalence. In this paper we formulate a multi-shot problem, where the extended posterior obtained after one update is used again as the prior for the next update. We first define a formal notion of $n$-shot equivalence and derive several propositions for arbitrary extended beliefs. We then argue that the agent must also specify why the data obtained in different rounds concern the same underlying object. Through the quantum de Finetti representation, this narrows the one-copy belief to a special class: candidate-state ensemble belief. In that sector, we show that two beliefs are $n$-shot equivalent if and only if their $(n+1)$-th moments are equal. We also give a physical interpretation of this moment condition and illustrate it through the equivalence between Haar priors and projective-design priors at bounded update depth.

Optically addressable electron spin qubits that function at room temperature and under ambient conditions are essential for advancing quantum sensing. Solid state defect platforms offer robust spin-photon interfaces but lack precise defect positioning and electronic tunability. Molecular spin qubits enable bottom up chemical design yet suffer from limited photostability. Here, we introduce para-halophenyl (-Cl, -Br and -I) quantum defects in (6,5) single wall carbon nanotubes that trap triplet excitons with a spin-photon interface that is operable under ambient, room temperature conditions. These defects were shown to emit in the near infrared within the biological transparency window, and their placement on the nanotube surface provides nanoscale proximity to target environments. The deep optical traps formed by the defects yield exceptional photostability. Here, we demonstrate optical initialization and readout of these triplet states at room temperature, provide proof of principle sensing of paramagnetic molecules, and highlight potential for on chip detection. Together, these results establish SWCNT defects as a promising new platform for future quantum sensing.

Coherent multidimensional spectroscopy probes interactions and dynamics of molecular systems through nonlinear optical signals. Quantum light excitation has been explored as a means of controlling these signals, raising the question of how excitation-light correlations affect the precision of molecular parameter estimation from the emitted signal. In this work, we show that photon-number correlations and two-photon coherence play distinct roles in encoding molecular information in the emitted rephasing signal. In the weak-emission regime and within the single Schmidt pair approximation, we derive a normally ordered information law in which the joint photon-number moment and the squared magnitude of the two-photon coherence weight the amplitude and phase sensitivities of the molecular response, respectively. For matched temporal modes and mean photon numbers in each input mode, two-mode squeezed vacuum enhances both weights relative to coherent excitation, whereas independent displaced squeezing preserves the amplitude weight but reduces the phase weight. The background population and its parameter dependence also affect the total quantum Fisher information, which therefore cannot be inferred from the coherent mean-field signal alone. We derive a leading-order bound on its enhancement over coherent excitation when the background population is nonnegative and common to the compared sources. These findings provide criteria for selecting excitation sources according to how the target molecular parameter affects the amplitude and phase of the response.

Controlling transition rates is a central objective across quantum optics, condensed-matter physics, and chemical physics, encompassing processes such as spontaneous emission, energy and charge transfer, spin relaxation, and chemical reactions. Although Fermi's golden rule provides a powerful framework for calculating such rates of weakly coupled transitions, conventional calculations require the interaction to be specified in advance; the range of rate responses attainable over a broader interaction space remains unknown. We formulate spectral-overlap golden-rule rates as quadratic forms of the interaction and derive rigorous bounds on rate modulation over a specified interaction space. As an example, application to energy transfer from a donor to a molecular vibration coupled to an optical cavity reveals that enhancement and suppression depend jointly on the interaction and cavity detuning, including continuous reversal of the rate response for a fixed interaction. The same approach may elucidate rate control for other golden-rule processes, including excitation-energy transfer, nonadiabatic electron transfer, nonradiative electronic transitions, vibrational and spin relaxation, and spontaneous emission.

This work revisits the debate on fractional uncertainty relations that arose a decade ago and tries to settle it. After a careful study of the position-momentum uncertainty product of the Lévy wave packet, a novel lower bound is proposed for uncertainty relations in fractional quantum mechanics. This bound is nearly linear in the Lévy index and is satisfied by exact, calculable solutions available in the literature.

In this work, we investigate the convergence rate of the quantum Blahut-Arimoto (BA) algorithm proposed for computing the coherent information of less noisy quantum channels. Previous work established exponential convergence under certain restrictive assumptions on the channel. Using a Taylor expansion around a positive definite optimizer, we show that, for an injective degradable channel whose degrading channel has a relative-entropy contraction coefficient strictly less than one, the algorithm converges at an exponential rate after sufficiently many iterations. We further verify this condition for qubit amplitude-damping (AD) channels in the relevant parameter regime. In addition, by analyzing the Bogoliubov-Kubo-Mori (BKM) metric on the Bloch ball, we derive an explicit characterization of the relative-entropy contraction coefficient of qubit AD channels. The proposed approach is further extended to calculate the relative contraction coefficient and the relative expansion coefficient of two qubit AD channels.

We present an error-controlled framework for the quantum simulation of non-Markovian open-system dynamics in Gaussian environments. For a system coupled linearly to a Gaussian environment with zero mean, the bath's influence on the reduced dynamics is completely determined by its two-time correlation kernel. This allows us to replace the microscopic environment with an equivalent bath that has the same kernel. On a finite simulation interval, a rank-$N$ approximation of the kernel yields an effective bath of $N$ bosonic modes with time-dependent couplings to the system. To encode these modes in qubits, we first truncate each mode to its lowest $d$ occupation levels. When stronger couplings lead to large occupations, we introduce coupling dilution, which replaces each mode with several more weakly coupled copies while preserving the bath correlation kernel. This distributes excitations across more modes and trades additional modes for smaller local dimensions. We derive explicit reduced-state error bounds and establish polynomial circuit width and depth in simulation time and inverse accuracy under stated spectral-decay and coupling-regularity assumptions, provided elementary unitaries admit polynomial-cost implementations.

The Fröhlich-Pizzo (FP) model is a quantum-mechanical model originally developed to describe the interaction between an atom and the electromagnetic field in the nonrelativistic limit $c\to\infty$. We show that an adaptation of the FP model based on the local algebras of a $U(1)$ chiral current captures essential features of the horizon-induced decoherence mechanism identified by Danielson, Satishchandran, and Wald (DSW) in the limit of large holding time $T$. Our analysis suggests that the effective dynamics of the system undergoing decoherence in the DSW setting retains non-Markovian features. Our approach also offers a glimpse into the possible role of quantum events in the dynamics underlying horizon-induced decoherence.

We investigate spin-resolved momentum distributions and phase vortices in multiphoton electron-positron pair production within a modified two-level model. This model retains the diagonal spinor inner-product terms neglected in the adiabatic approximation, thereby inducing spin-resolved transverse asymmetries in the momentum distribution. For a circularly polarized pulse, the handedness determines the winding direction of the quantized vortices, whereas for a linearly polarized pulse, the phase distribution exhibits nodal lines rather than quantized vortices. For two time-delayed circularly polarized pulses, the time delay introduces a relative phase that governs the multiphoton interference, which in turn drives the vortex evolution in each spin configuration. These results demonstrate that pulse polarization and time delay enable coherent control over vortex topology in pair production.

We theoretically investigate the interplay of topology and localized non-Hermiticity in a finite Su-Schrieffer-Heeger chain characterized by non-Hermitian potentials at its boundaries. By tuning the boundary gain and loss parameters, we exploit the finite-size hybridization of two mid-gap topological edge states to analytically derive the exact coordinates of boundary-induced exceptional points (EPs), $Γ_{\rm EP}=\pm i v^{N}/w^{N-1}$, at which these states undergo coalescence. We demonstrate that dynamically encircling these boundary EPs facilitates a robust, chiral edge state-transfer protocol. Depending on the orientation of the encircling loop, this protocol allows a topological edge state localized at one boundary to be either transferred to the opposite edge with perfect fidelity or returned to its starting position through a double switching process. Importantly, since the non-Hermiticity remains strictly confined to the boundaries, this chiral transport occurs without affecting the energy spectrum of the bulk bands. These results establish a minimal framework for a large-scale topological chiral switch that is experimentally verifiable and capable of being controlled through boundary non-Hermitian driving.

Dense ensembles of nitrogen-vacancy (NV$^-$) centres in nitrogen-rich diamond dephase on the electron spins of the substitutional nitrogen (P1) centres. If the paramagnetic nitrogen is instead converted into NV$^-$ centres, the laser that initializes the sensor also pumps the bath into $m_s$ = 0, a state with no moment along its own axis. Using cluster-correlation-expansion (CCE) calculations, combined with an exact solver for probe-bath exchange and with no adjustable parameter, this paper asks whether such an optically polarized NV$^-$ bath dephases a sensor more slowly than a P1 bath of the same density. The answer is set by the field. In a field along [111], three quarters of the bath centres lie off the field axis, and the moment of their $m_s$ = 0 state along the field grows from 0.04 at 25 G to 0.46 at 300 G and 0.81 at 800 G. At 25 G the polarized bath is therefore nearly silent: at $10^{17}$ cm$^{-3}$ the dephasing time $T_2^*$ of a separately addressed $^{15}$NV$^-$ probe is 112 us, six times the 18.1 us of a P1 bath, and still 2.4 times at 90 % polarization; an ensemble measurement gains a factor of two. At 300 G the advantage over P1 shrinks to 1.4, and at 800 G the polarized bath dephases faster than P1. The field dependence of every bath, P1 included, follows the mean moment of its centres along the field. For the Hahn echo, exchange with on-axis bath centres and bath relaxation ($T_1$ = 6 ms) limit the gain to 1.2 times the P1 value at 25 G. Optical polarization of an NV$^-$ bath at low field therefore offers dephasing times beyond the P1 limit of nitrogen-rich diamond.

A quantum computer could recover the key of any Ethereum account whose public key appears on chain. We prove that no sidechain or bridge that leaves Ethereum's rules unchanged can protect such accounts: their funds must move into a contract whose release condition relies only on quantum-safe primitives. We design \emph{PQ-Vault}, a custody system for unmodified Ethereum combining this vault, a quantum-safe proof-of-stake sidechain whose checkpoints carry compact certificates, and an optimistic dispute protocol. We give the first security proof of compact certificates against quantum attackers and a matching attack: with classically chosen parameters, the guarantee falls from 128 to about 60 bits, and a simple rule restores it. We show that a common seed-update rule in hash-chain proof of stake lets an attacker steer chosen slots and profit from splitting its stake, and give an election whose steering gain and inclusion delay are provably bounded against quantum attackers. Since compressing certificates with a pairing-based SNARK breaks quantum security, we use fraud proofs that need a single signature check. For 65,536 validators, a certificate is 0.8 MB, 260 times smaller than all signatures, and verifies in about 20 ms; the vault accepts a checkpoint for about 420,000 gas.

Kelvin waves carry energy along vortices, but their resonant interactions contain information that is absent from the linear spectrum. We identify a geometry that exposes this information on a vortex surface in four spatial dimensions. Perpendicular incoming waves cancel the complete local-area four-wave coupling, leaving the finite nonlocal interaction mediated by the surrounding fluid. This interaction restores conversion at generic wave-number ratios, yet changes sign and vanishes at a selected ratio while momentum and frequency remain exactly matched. Matching to Gross-Pitaevskii (GP) theory, including the microscopic core response, establishes a zero of the full coupling at every sufficiently small nonzero wave number, with ratio tending to $λ_*\simeq1.469$. Finite-grid GP coefficients exhibit a sign reversal for the same resonant quartets. Separate coherent-mixing calculations and weak-probe spectra connect the coupling sign to the generated-wave phase and the ordering of reflection-even and reflection-odd modes. The resulting suppression removes a leading channel for changing propagation directions without changing the paired wavelengths. These results isolate a nonlinear effect of the surrounding flow that local tension misses, providing a microscopic benchmark for vortex-wave theories and a starting point for studying angular redistribution beyond the Kelvin spectrum.

The solution of combinatorial optimization problems by means of quantum annealing is based on the preparation of an equally superposition state. Such superposition is crucial to the associative memory problem of correctly recalling patterns. In this paper, we study the alignment of the amplitudes of stored states in memory using the proposed auxiliary Hamiltonian, which is switched off at the end of evolution. The results of the algorithm execution were obtained both by numerical modeling and by the perturbation theory method, which made it possible to obtain the dependences on physical parameters in explicit form. As examples, systems of two and three qutrits, represented by spins S=1, are considered. Since the Hamiltonian is expressed in a univer-sal form through projectors onto states stored in memory, it can be used for other quantum sys-tems (platforms).

A circuit parameter can change measured features without changing their projected Gaussian kernel. We characterize this lost dependence and distinguish recovery by metric design from nonlinear feature expansion. With analytic feature coefficients, a fixed finite data basis affinely independent on the input domain, a fixed positive definite metric, and fixed bandwidth, the coefficient Gram matrix determines all-input kernel equivalence, global coordinate inactivity, and generic differential rank. An exact four-qubit family exhibits a sharp boundary: diagonal metrics give rank two, dense metrics reach but cannot exceed three, and no fixed affine expansion crosses this ceiling. One appended nonlinear scalar coordinate suffices for rank four and is minimal when the original features are retained. A single pairwise product achieves this with an explicit nondiagonal metric; a scalar sum of two products achieves it with a diagonal metric. Both use existing ideal local means. Exact certificates establish ranks in 54 selected circuit/readout settings. Matched finite-shot comparisons show that minimal representation size need not give the best sensitivity among the tested designs. Under a factorized measurement distribution, conditional product estimation cannot increase variance at a fixed design. Execution audits further separate kernel identifiability from compiled cost.

Selecting an effective quantum compiler configuration requires coordinated decisions over both hardware targets and compiler settings, with the ultimate goal of improving circuit execution fidelity. Existing SOTA approaches typically decompose this problem into two sequential stages: a device is chosen first, after which compiler options are tuned on that device through RL-based search. This bottom-up strategy can be fundamentally limited by its initial device decision, since a poorly matched backend may constrain the best fidelity achievable regardless of how effectively later compiler options are optimized. In contrast to classical compiler tuning, where the search space is often prohibitively large, the configuration space of quantum compilers remains manageable enough to support exhaustive search. Consequently, rather than repeatedly searching from candidate configurations, one can derive reusable configuration knowledge from offline oracle results and apply it directly to new circuits. In this paper, we introduce a top-down configuration-selection paradigm and build QuOPTBench, an exhaustively searched benchmark containing oracle configurations for 268 quantum circuits. We first study whether LLMs can directly infer suitable configurations and evaluate ten representative LLMs. The results reveal that vanilla LLMs remain far from the oracle. We then employ an LLM to extract transferable rules from sampled circuits governing configuration selection. Using these rules together with predictors trained on the enumerated configuration data of the sampled circuits, we design QuTOP, a rule-guided ML framework that performs fast configuration selection without iterative online search. Across our evaluation, the distilled rules consistently strengthen LLM-based selection, while QuTOP provides the strongest overall balance between solution quality and selection latency among the baselines.

Quantum Fisher information (QFI) is a fundamental quantity in quantum information and quantum mechanics, and evaluating it in various physical systems has become an important research topic. However, its evaluation in large systems still faces many challenges. Hereby we propose an ancilla-based protocol for evaluating the QFI of large systems and establish the conditions under which this protocol can ``perfectly'' evaluate the QFI in theory. As a demonstration, the protocol is applied to quantum circuits to evaluate the QFI of the Greenberger-Horne-Zeilinger state.

Quantum circuit optimization is a key step toward the efficient execution of quantum algorithms. Template matching has emerged as one of the dominant approaches for simplifying quantum circuits, yet it confronts the intrinsic challenge of accommodating gate commutativity. The state-of-the-art template-matching algorithm relies on a directed acyclic graph (DAG) representation. While this DAG-based technique handles gate commutativity satisfactorily, it fails to preserve the local connectivity inherent to quantum circuits, thereby leading to relatively high matching complexity. In this paper, we introduce a hypergraph representation (HG), a commutativity-aware representation that collapses commuting gates into a single super-node while retaining all local connectivity. This enables matches to be extended locally without revisiting the rest of the circuit, with incremental updates limited to the immediate neighborhood. Experimental results demonstrate that our HG matcher achieves 11--606x speed-up over the DAG-based implementation in Qiskit (Iten et al., 2022) on both random and arithmetic benchmarks, while maintaining the same optimization quality. The acceleration increases with circuit size, confirming that preserving locality and connectivity is the key to scalable quantum circuit optimisation.

We derive sufficient criteria that guarantee convergence of open quantum system dynamics to a unique long-time state independent of the initial conditions. We refer to this behavior as complete relaxation. Focusing on systems described by Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) master equations on finite-dimensional Hilbert spaces, our approach uses only elementary mathematical arguments. For autonomous systems, we recover three previously derived relaxation criteria, which can be expressed as algebraic conditions on the Lindblad operators and the Hamiltonian entering the GKSL equation. For periodically driven systems, we obtain a new criterion involving a similar algebraic condition and a local continuity requirement on the time-dependent GKSL generator. This result implies an earlier criterion for complete relaxation formulated in Ref. [J. Phys. A 52, 43LT01 (2019)]. We also discuss implications of our approach for periodically modulated classical master equations, as well as extensions to driven systems without a periodicity constraint.

A ligand can adopt multiple conformations within the same binding site, and these conformations can interact differently with the surrounding protein. Multiconformer modeling must therefore determine which candidate conformations to retain and what occupancies to assign to them. An established automated approach uses mixed-integer quadratic programming (MIQP) with hard occupancy and conformer-count limits for this selection. Here, we reformulated conformer selection as a quadratic unconstrained binary optimization (QUBO) problem with finite penalties and discrete occupancies. We solved the QUBO using a quantum-classical hybrid solver. We compared this workflow with the MIQP-based qFit-ligand workflow across 83 paired X-ray ligand entries using the same experimental inputs and the same qFit-ligand processing protocol. For each entry, both final models were evaluated against the same composite-omit map generated from the common input structure before the two workflows diverged. Quantum-qFit produced higher ligand-region real-space correlation coefficients (RSCC) in 62 entries 74.7% and lower occupancy-weighted torsional strain in 66 entries 79.5%. Similar directional trends remained in the 28 entries with matched final conformer counts. The molecular Electron Density for Individual Atoms score (EDIAm) decreased in most entries. This result shows that higher regional map agreement did not necessarily correspond to stronger atom-level density support. Overall, the results show that the conformer-selection formulation can change which ligand states are represented from the same experimental data and provide a QUBO framework for studying multiconformer ligand selection.

Quantum Multi-Programming (QMP) enables the simultaneous execution of quantum circuits from multiple users on a single quantum chip in cloud quantum computing services. However, QMP is vulnerable to crosstalk attacks, in which a malicious user deliberately induces crosstalk to disrupt other users' computations. As a countermeasure, prior work has proposed the use of buffer qubits, which remain idle and are allocated between quantum circuits to suppress the effect of crosstalk. Nevertheless, to the best of our knowledge, such countermeasures have not been publicly reported in production quantum cloud software. In this paper, we extend the QMP of OQTOPUS, open-source software that is already in production use for operating real quantum computers, with a buffer-qubit-based circuit allocation method. Experiments on a real device characterize the attack effect in terms of energy relaxation and dephasing, showing that observable degradation appears in dephasing characteristics of qubits adjacent to the attacker circuit. Based on this result, we release the proposed method as part of OQTOPUS and confirm that the buffer qubits are correctly reserved around the allocated circuits.

Reaching a degenerate ground-state manifold and sampling it uniformly are distinct properties of a quantum annealer. We quantify this distinction using an Ising ring with additional couplings between maximally separated sites. For antiferromagnetic benchmark couplings and $N \geq 5$, we derive the exact ground-state energy, degeneracy, and defect structure for each congruence class of $N$ modulo four. This classification separates ground-state hit probability from conditional sampling bias. We embed instances with up to 162 logical spins on a D-Wave Advantage processor using length-two chains and compare its output with simulated annealing on the embedded and logical problems. For a frustrated $N=83$ instance, the processor visits 164 of the 166 exact ground states, yet the conditional distributions over states and defect sectors remain nonuniform. For $N=160$, the processor has a larger ground-state hit probability than logical simulated annealing (0.869 versus 0.519), but also a larger total-variation distance from uniformity (0.317 versus 0.136). A pause during the anneal raises the ground-state hit probability from 0.42 to 0.86 without restoring uniform sampling. These results identify a relaxation window and demonstrate that optimization success and sampling quality need not improve together, providing an exactly characterized benchmark for open-system quantum annealing.

Taiyi Quantum, a Shanghai-based quantum hardware developer, has secured over ¥1 billion RMB (approx. $149.6M USD) in cumulative funding within nine months of its founding, achieving unicorn valuation status. The company specializes in Ytterbium neutral-atom arrays for fault-tolerant quantum computing and has made significant progress in hardware integration and open-sourced its LUOSHU compiler. The post Taiyi Quantum Surpasses ¥1 Billion RMB ($149.6M+ USD) in Cumulative Funding for Ytterbium Neutral-Atom Systems appeared first on Quantum Computing Report .

Insider Brief Vietnamese quantum expert Nguyen Luong Quang recommends closer EU partnerships to develop Vietnam’s quantum workforce, research infrastructure and industrial capabilities. His proposal identifies joint training, remote access to European quantum computers and participation in software, optical component and specialized chip supply chains. The recommendations build on broader EU–Vietnam cooperation but do not constitute an approved quantum agreement or funding commitment. Vietnam should make European partnerships a central part of its quantum technology development, using joint research, specialist training and access to computing infrastructure to build domestic capabilities, a Vietnamese expert has proposed. Nguyen Luong Quang, a member of the Vietnam Quantum Technology Network , or VNQuantum , outlined the approach in an interview with the Vietnam News Agency’s Brussels correspondent, according to VietnamNet Global . His recommendations would connect Vietnam’s emerging quantum sector more closely with European research institutions and technology businesses. The proposal comes as Hanoi and Brussels deepen their political and scientific relationship. The two sides upgraded relations to a Comprehensive Strategic Partnership in January, creating a broader framework for cooperation. In May, the European Commission and Vietnam’s Ministry of Science and Technology signed a letter of intent to strengthen research and innovation ties . The agreement aims to expand researcher exchanges, knowledge sharing and connections among universities, startups, industry and public institutions, according to the commission. Those arrangements provide a potential foundation, or framework for the deeper quantum cooperation that Quang advocates. Quang recommended closer ties with France, Germany, the Netherlands, Finland and Spain, including postgraduate training and pilot applications in banking, energy and cybersecurity. Connecting domestic laboratories with remotely acces

Insider Brief Finland’s Coherence Quantum raised €2.78 million in seed funding to develop cryogenic signalling and control infrastructure for scaling solid-state quantum computers. The Aalto University spinout is developing signal conditioning and higher-density interfaces to manage wiring, heat and noise as qubit counts increase. Lifeline Ventures led the round, with participation from Mårten Mickos , to fund an Espoo laboratory, product prototypes, manufacturing development, research and hiring. Image: Coherence Quantum founding team. (Provided) PRESS RELEASE &#8212; Coherence Quantum , a Finnish quantum hardware company originating from Aalto University’ s Quantum Computing and Devices (QCD) group, has raised €2.78 million in seed funding to develop a new approach to the cryogenic infrastructure surrounding solid-state quantum processors. The €2.78 million round is led by Helsinki-based early-stage investor Lifeline Ventures , with participation from technology entrepreneur Mårten Mickos . Quantum computers are being developed to tackle calculations that are beyond the practical reach of today’s computers, with potential applications ranging from discovering new materials and medicines to modelling complex physical systems. Reaching that point will require machines with far more usable qubits than today’s systems. But adding more qubits creates another scaling problem: everything needed to control them. As quantum processors grow, more control and readout signals need to reach the quantum processing unit (QPU). Conventional approaches require more wiring and signal-conditioning hardware inside a system with very limited space and cooling power. At the same time, the qubit environment has to remain protected from thermal noise and other disturbances that can affect performance. Coherence Quantum is developing an integrated cryogenic signalling and control platform to address this scaling challenge. Its first technologies focus on cryogenic signal conditioning, hel

For scientists, breakthroughs often stem from unexpected turns. A research team led by Oscar Dahlsten, an associate professor in the Department of Physics at City University of Hong Kong (CityUHK), set out to prove a theoretical limitation, only to discover a quantum solution. The finding breaks traditional physical constraints and introduces a strategy for harvesting energy from fluctuating sources.

Insider Brief Postquant Labs has launched its Quip Virtual Machine (QVM) on the Aglais testnet, providing a shared programming and execution environment for quantum and classical computing systems. The QVM supports a constraint-based programming language, a compute-credit pricing model and a verification system for results, while researchers at Monash University , the University of Notre Dame and Purdue University assess the platform. In a demonstration at Quantum.Tech World, the QVM ran 1,930 portfolio optimization comparisons in which its quantum solver matched or outperformed the classical solver under the company&#8217;s stated evaluation criteria, with both typically returning results in 0.1 to 0.3 seconds. PRESS RELEASE &#8212; Postquant Labs , developer of the quantum computing marketplace quip.network , has launched its Quip Virtual Machine (QVM) and first quantum smart contracts. The QVM is live today on the Aglais testnet at aglais.quip.network &nbsp;and provides a shared programming and execution environment for quantum and classical computing, with support for the leading quantum hardware platforms. Researchers from Monash University , the University of Notre Dame , and Purdue University are currently assessing the QVM, while SiC Systems is exploring the QVM&#8217;s potential to address complex industrial optimization problems, including applications in AI-driven manufacturing and the design, control and operation of chemical and biological processes. In a live demonstration &nbsp;at Quantum.Tech world, the QVM ran 1,930 head-to-head portfolio optimization races between quantum and classical solvers, using problems created by around 100 visitors. Results within 0.5% of each other were treated as ties. The quantum solver matched or beat the classical solver in every race, and in every race where the results differed by more than 0.5%, the quantum solver produced the better portfolio, by a median of 2.56%. Both solvers typically returned answers in 0.1 to

Insider Brief Monarch Quantum is supplying integrated photonics hardware to support Infleqtion &#8216;s work on NASA&#8217;s Quantum Gravity Gradiometer Pathfinder mission, backed by a $20 million follow-on contract. The mission, led by NASA&#8217;s Jet Propulsion Laboratory, aims to demonstrate a space-based quantum gravity gradient sensor, with the next phase focused on hardware development and testing. The technology could inform future gravity-mapping systems that measure changes in groundwater, ice, natural resources and other geophysical conditions, with instrument development targeting a 2030 launch. PRESS RELEASE &#8212; Monarch Quantum extends congratulations to Infleqtion on receiving the $20 million NASA follow-on contract supporting the Quantum Gravity Gradiometer Pathfinder (QGGPf). Led by NASA&#8217;s Jet Propulsion Laboratory in Southern California, the mission is anticipated to demonstrate the world&#8217;s first space-based Earth quantum gravity gradient sensor. The award advances the mission into its next phase of hardware development and testing. Monarch Quantum supports Infleqtion &#8216;s efforts on the mission by supplying integrated photonics hardware that delivers precise, stable light required to meet the performance of the sensor. &#8220;NASA&#8217;s continued investment in this pathfinder mission validates the progress being made to move quantum sensing beyond the laboratory and into demanding operational environments,&#8221; said Tim Day, Chief Executive Officer and Chairman of Monarch Quantum . &#8220;Space-qualified quantum systems require exceptional systems engineering paired with reliability and precision. We are proud to support Infleqtion and NASA in advancing the photonics subsystems needed to make this mission possible.&#8221; QGGPf is designed to demonstrate quantum sensor technologies that could inform future gravity-mapping instruments in low-Earth orbit. By measuring subtle variations in Earth&#8217;s gravitational field, fut

Insider Brief Project Eleven and Relm Insurance have partnered to explore how post-quantum security controls could inform digital asset insurance underwriting and risk assessments. Relm will advise on Strongpoint, Project Eleven &#8216;s institutional custody product, with a focus on key exposure, signing systems, transaction approvals, migration readiness and third-party dependencies. The collaboration is exploratory, and any future effects on insurance underwriting or premiums will require further evaluation and remain subject to Relm&#8217;s independent underwriting processes. PRESS RELEASE &#8212; Project Eleven , the post-quantum security company for digital assets, today announced Relm Insurance &nbsp;as a development partner for Strongpoint , its flagship institutional custody product. The collaboration will explore how an institution&#8217;s post-quantum security controls could be evaluated within digital asset insurance underwriting, helping both companies better understand how quantum readiness may influence future assessments of digital asset risk. As quantum computing advances, a sufficiently powerful machine could derive private keys from exposed public keys and compromise digital assets. Institutions need custody infrastructure capable of adapting its cryptography before such a machine becomes available. Strongpoint is built for that transition. The platform combines classical and post-quantum signing and separates institutional controls from the cryptography layer, enabling institutions to replace signing algorithms while preserving approval rules and audit history. &#8220;Every institution holding digital assets will eventually need to prepare for post-quantum cryptography. The open question is whether that transition happens on the institution&#8217;s schedule or under pressure,&#8221; said Alex Pruden, CEO and Co-Founder of Project Eleven . &#8220;Insurance plays a critical role in how markets assess and manage risk. We believe there is an opportun

Insider Brief Bechtle will provide the German Aerospace Center’s Quantum Computing Initiative with cloud access to IQM ’s superconducting quantum computers until June 2027, expanding its research resources and technology portfolio. The agreement enables application teams to develop and run quantum algorithms and compare superconducting systems with other quantum computing technologies. Bechtle will manage platform accounts and support, while a dedicated classical server at IQM ’s Munich data center will support hybrid quantum and classical workloads. PRESS RELEASE &#8212; Under a new framework agreement, Bechtle is providing German Aerospace Center ’s Quantum Computing Initiative (DLR QCI) with cloud-based computing time on quantum systems from IQM Quantum Computers. This expands the DLR QCI’s quantum computing resources for its application teams, complements its existing technology portfolio, and creates additional opportunities for comparison with quantum systems already in place. The IQM Resonance cloud platform supports efficient use through seamless user and group management and provides the foundation for planning, developing, running, and managing quantum algorithms across the entire development process. “ Our offering combines technological excellence with the flexibility that benefits the DLR QCI in its quantum computing applications. This is how we support the customer in expanding its research infrastructure, while also strengthening the technological sovereignty of Germany and Europe in international competition, ” says Christian Behma, Managing Director of Bechtle IT System House Bonn. The DLR QCI brings together start-ups, industry, research, and the public sector in a strong ecosystem for sovereign, competitive quantum computing. To this end, it commissions companies to develop quantum computers, quantum algorithms, and relevant use cases. The focus is on practical application scenarios, for example in materials research, aerospace, mobility, and secu

Quminex, a Quebec-based exploration technology startup, has successfully raised $1.5 million CAD (approximately $1.06 million USD) in pre-seed funding. This investment, led by Quantacet and QAI Ventures, will accelerate the commercial development and field deployment of its proprietary Quminex Discovery Platform™. The platform aims to modernize mineral discovery by using machine learning and high-performance computing to transform geological data into explainable mineral system models. The post Quminex Raises $1.5M CAD ($1.06M USD) Pre-Seed Round Led by Quantacet and QAI Ventures to Advance Mineral Discovery Platform appeared first on Quantum Computing Report .

For nearly a century, physicists have relied on the Born rule to calculate the chances of different outcomes when they measure a quantum system. Yet despite decades of effort, nobody has managed to derive the rule from more basic mathematical principles without making assumptions about probability along the way.

Light is one of the most powerful tools scientists have for probing matter. By interacting with electrons, light reveals how atoms, molecules and materials are structured and how they evolve in time. Highly energetic ultraviolet and X-ray photons are particularly attractive because they can access electrons located close to atomic nuclei, where each chemical element carries its own distinctive electronic fingerprint.

Insider Brief Arqit Quantum has made a strategic investment in Sirius Computer to support the development of quantum-safe communications for defence, government and national security users. The companies are developing Crux, a software-based connectivity platform that combines Sirius’s secure networking technology with Arqit ’s Sovereign Key Platform and NetworkSecure adaptors. The investment will support product development and integration, while the companies pursue secure networking opportunities with NATO member countries, the UK Ministry of Defence and the US Department of Defense. PRESS RELEASE &#8212; Arqit Quantum Inc. (NASDAQ: ARQQ), a global leader in quantum-safe encryption helping safeguard sensitive information from current and future cyber threats, today announced a strategic investment in Sirius Computer, Inc., a technology provider of secure computing and networking solutions for defence, intelligence and critical national infrastructure. This will accelerate the development and delivery of quantum-safe communications for defence, government and national security users. The investment builds on an existing partnership that combines Sirius’s secure networking technology with Arqit ’s Sovereign Key Platform (SKP) and NetworkSecure adaptors to deliver Crux, a software-based connectivity platform. The companies&#8217; joint offering protects sensitive communications across devices and networks, helping defence users share information securely in deployed environments, and when operating alongside allied forces. The software-based offering is designed to run on commercial devices and work alongside existing infrastructure, enabling users to extend secure communications without replacing their underlying networks. Applications include mobile devices, cloud and network systems, autonomous platforms such as Uncrewed Autonomous Vehicles (UAVs) and their associated control systems. The strategic investment will support the continued development of Crux and Sir

Transmitting electricity without losing any energy may sound impossible, yet this is precisely the promise of superconductivity. For nearly 40 years, scientists have been working to understand materials that exhibit this remarkable property at relatively high temperatures. Unlocking their secrets could one day help make power grids more efficient, enhance medical technologies and support the development of quantum computing.

Tiny atoms and molecules are constantly bombarding each other all around us. While we regularly measure the large-scale effects of these interactions, measuring the effect of each individual collision is far more difficult. But now, researchers have managed to measure how tiny gas particles affect a single silica particle in the lab. In their new study, published in Physical Review Letters, the team describes how they detected the momentum transfers of individual collisions of gas particles with a nanoparticle levitated in laser light.

Insider Brief Alice &amp; Bob reported Phase 1 PROQCIMA results demonstrating core components of its cat-qubit error-correction architecture on three hardware demonstrators. Tests included protected CNOT gates, repeated error-correction cycles and a non-Clifford gate, but the measured logical error rate remained above the error-correction threshold. A digital twin identified longer, more consistent qubit coherence as a priority, while automated monitoring software tracked performance and recalibration needs. PRESS RELEASE &#8212; – Alice &amp; Bob , a leader in fault-tolerant quantum computing, today shares a summary of results from Phase 1 of PROQCIMA , the French government’s quantum computing programme. Led by the French Defense Innovation Agency (AID) and the Direction générale de l&#8217;Armement, PROQCIMA aims to develop two prototypes of universal quantum computers, each capable of supporting 1,000 logical qubits, ready for industrialisation by 2032. The programme is structured as a 10-year competition: three candidates will continue after the first four years, with two ultimately selected to continue beyond year eight.&nbsp; Five companies were selected to participate: Alice &amp; Bob , Pasqal , Quandela , Quobly and C12 . The first phase of the programme was designed to assess the technical and industrial feasibility of each company’s approach. Each candidate was required to demonstrate the expected level of technological maturity, including through the development and testing of its technology on real hardware. Alice &amp; Bob began work on Phase 1 of PROQCIMA in 2024, committing to build an integrated multi-block demonstrator with partial functional validation to demonstrate the core operations of its error-correction architecture on real hardware. Alice &amp; Bob has delivered on that commitment. The company assembled and operated three independent demonstrators, two on 6-qubit chips and one on a 12-qubit chip. The team demonstrated each building block o

Insider Brief The BIRD Foundation has approved $7.4 million in conditional grants for seven joint U.S.-Israel R&amp;D projects, with total investment expected to reach $20 million, including private-sector funding. The selected projects cover quantum computing, satellite communications, semiconductor memory, AI-driven cancer detection, precision agriculture, digital pathology and medical 3D printing. The quantum computing project pairs Israel&#8217;s Qarakal Quantum with U.S.-based Quantum Elements to develop a minimum viable product for mapping complex surface-catalysis reactions using quantum computing. PRESS RELEASE &#8212; In September 2026, the Board of Governors of the Israel-U.S. Binational Industrial Research and Development ( BIRD ) Foundation approved $7.4 million in conditional grants for seven joint R&amp;D projects between U.S. and Israeli companies. Including private-sector investment, total investment in the projects is expected to reach $20 million. The BIRD Foundation supports strategic collaborations between U.S. and Israeli companies to jointly develop innovative products and technologies for global markets. In addition to providing conditional grants of up to $1.5 million per project, the Foundation helps companies identify suitable partners and build cross-border collaborations. Projects submitted to BIRD are evaluated by BIRD staff and by expert reviewers appointed by the National Institute of Standards and Technology (NIST) of the U.S. Department of Commerce, and by the Israel Innovation Authority. The seven newly approved projects bring the total number of BIRD -supported collaborations to more than 1,200 since the Foundation&#8217;s establishment in 1977. To date, BIRD has invested approximately $470 million in joint projects, helping generate more than $10 billion in direct and indirect revenue. The newly approved projects are: Ibex Medical Analytics (Tel Aviv, Israel) and Proscia (Philadelphia, PA) will develop an AI-based precision oncolo

Insider Brief A NowSecure analysis of 136,711 iOS and Android apps found that 96.9% contained no detectable post-quantum cryptography (PQC)-related code or libraries. The analysis also identified weak encryption algorithms in more than 3,100 mobile apps, pointing to existing cryptographic weaknesses alongside future quantum-related risks. NowSecure recommends that organizations inventory cryptography in first- and third-party mobile apps, remediate vulnerable implementations and retest applications as part of a planned PQC migration. PRESS RELEASE &#8212; NowSecure today released an analysis, conducted with NowSecure Platform, of 136,711 iOS and Android apps. It found that 97% contain no detectable post-quantum cryptography (PQC), the new generation of encryption standards designed to withstand attacks from quantum computers. Even among the most popular U.S. apps, fewer than 1 in 10 showed quantum-safe code. Security teams often leave mobile apps out of their cryptographic inventories, and organizations cannot migrate what they have not inventoried.&nbsp; The risk does not wait for quantum computers. Using runtime testing, NowSecure flagged weak encryption algorithms in more than 3,100 Android and iOS apps during the same study. These checks detect legacy algorithms such as DES and RC4. The findings highlight the need to address existing encryption weaknesses while identifying and migrating public-key cryptography vulnerable to future quantum attacks.&nbsp; Q-Day Is Close, and Migration Takes Years&nbsp; According to Gartner®, Q-Day is “the moment that state actors obtain a cryptographically relevant quantum computer (CRQC),” and “Q-Day arrives as soon as 2029, but most progress on PQC migration so far is inadequate.”¹ Gartner warns that such capabilities “threaten widely used public-key cryptography” and says the business risks include “harvest now, decrypt later”.¹&nbsp; Because mobile applications transmit sensitive data over diverse public cellular and roaming n

We study the error-correction properties of multi-mode Fock-state codes under amplitude-damping (AD) noise, focusing on the asymptotic regime in which the total excitation of the code states grows without limit and the number of photon losses induced by the noise scales linearly with it. In this setting, existing code families, which correct only sublinearly many photon losses, do not protect against amplitude-damping (AD) noise with a constant loss parameter. As our main result, we address this gap by constructing asymptotically good Fock-state codes relying on random classical codes in the discrete simplex. Unlike many standard constructions of random quantum codes, our construction introduces randomness through the underlying classical indexing structure. Randomization also enables another desirable feature: bounded per-mode occupancy, which limits the number of photons in any individual mode and thereby increases the coherence lifetime of the code states. Finally, via a relation between Fock-state codes and permutation-invariant codes, our results also yield asymptotically good families of qudit permutation-invariant codes as well as codes in monolithic nuclear state spaces.

We consider the problem of testing and learning from data in the presence of resource constraints, such as limited memory or weak data access, which place limitations on the efficiency and feasibility of testing or learning. In particular, we ask the following question: Could a resource-constrained learner/tester use interaction with a resource-unconstrained but untrusted party to solve a learning or testing problem more efficiently than they could without such an interaction? In this work, we answer this question both abstractly and for concrete problems, in two complementary ways: For a wide variety of scenarios, we prove that a resource-constrained learner cannot gain any advantage through classical interaction with an untrusted prover. As a special case, we show that for the vast majority of testing and learning problems in which quantum memory is a meaningful resource, a memory-constrained quantum algorithm cannot overcome its limitations via classical communication with a memory-unconstrained quantum prover. In contrast, when quantum communication is allowed, we construct a variety of interactive proof protocols, for specific learning and testing problems, which allow memory-constrained quantum verifiers to gain significant advantages through delegation to untrusted provers. These results highlight both the limitations and potential of delegating learning and testing problems to resource-rich but untrusted third parties.

We introduce a numerical framework for reliably estimating conditional von Neumann entropies, a central quantity in device-independent quantum cryptography and randomness generation. Our method is based on semidefinite relaxations derived from the Navascués--Pironio--Acín hierarchy and provides entropy bounds directly from observed statistics, assuming only the validity of quantum mechanics. The approach builds on a recent integral representation of entropy and substantially improves efficiency: it requires about half as many support variables as existing methods, while allowing these variables to be chosen projectively, leading to a significant reduction in runtime. These advances enable the practical certification of randomness and security even in noisy conditions, while integrating seamlessly with modern entropy accumulation theorems. Consequently, our framework becomes a versatile tool for quantum cryptographic protocols, broadening the possibilities for secure communication in untrusted environments.

Matter under extreme conditions behaves as a non-equilibrium, strongly-interacting quantum system. Such systems are in the non-perturbative regime of quantum chromodynamics (QCD), where their time evolution is classically intractable. Quantum computing offers a promising alternative, but present-day devices are limited in qubit count and circuit depth, so efficient formulations and algorithms are key to scaling toward experimentally relevant QCD simulations. A scalable framework is established for simulating energy loss and hadronization in 1+1-dimensional SU(2) lattice gauge theory, in which a heavy quark traverses a lattice of light quarks. Classical lattice QCD methods are translated into physics-informed circuits to prepare the interacting ground state. The evolution is run on IBM's quantum processor ibm_pittsburgh, where the charge distribution and energy loss are measured. A further study develops the quantum simulation of the fully gauge-fixed SU(2) Hamiltonian in a mixed basis, a formulation that is expected to remain efficient at all gauge couplings. Digitizing the continuous gauge fields with as few as three qubits per plaquette reproduces low-energy observables with $10^{-3}$ precision. Scaling to larger systems is limited by resource overhead, which motivates truncations that preserve the relevant observables. Sequency Hierarchy Truncation (SeqHT) exploits the hierarchy in basis-operator contributions. Demonstrated on the adiabatic preparation of the $λφ^4$ ground state on ibm_sherbrooke, SeqHT reduces circuit depth by ~30%, suppressing hardware noise in the extracted observables. All simulations in this dissertation are validated on quantum hardware against classical benchmarks. These studies advance quantum simulations of real-time QCD dynamics.

As quantum computing moves from the noisy intermediate-scale quantum (NISQ) era toward early fault-tolerant quantum computing (EFTQC), quantum-enhanced AI is shifting from a conceptual idea to experimental research. Quantum components are expected to extend the capabilities of existing AI systems, yet it remains unclear how such components will help within large multimodal models. In this study, we try to answer that question for vision-language models (VLMs) using classically simulated quantum layers. With LLaVA-OneVision as the backbone, we evaluate 4- and 8-qubit basic-ring and strongly entangling circuits at four insertion and four replacement locations. Insertion adds quantum layers to the classical model, while replacement substitutes them for classical components. Using the same setup, we compare performance and computational cost between classical and quantum-classical hybrid models. On the Visual Spatial Reasoning dataset, inserting a quantum layer after the visual projector reaches 80.7% development accuracy, 2.28 percentage-points above classical full fine-tuning. Replacing the final decoder feed-forward sublayer retains 79.22% accuracy with 13.07 million fewer trainable parameters. Quantum insertion can thus improve accuracy, and selective replacement can reduce parameters. These benefits depend strongly on where the quantum layer is inserted or which classical component it replaces: earlier replacements lower accuracy, and fewer parameters do not reliably shorten training or reduce computation. To assess potential security benefits, we evaluated the robustness of quantum-classical hybrid models under six attack settings. Overall, our study maps where quantum layers help and hurt within VLMs, offering a starting point for hybrid VLM design; whether these gains generalize remains open. The code is available at https://github.com/TITANS-Lab-Artifacts/QuantumVLM.

This paper studies quantum spin systems: networks of spins coupled by local interactions. The Lieb-Robinson bound predicts that in these systems, information propagates at an essentially finite speed. We produce a new proof of this result. Our approach relies on a spectral bound on entries of resolvents of band matrices, the Combes-Thomas estimate, rather than on the standard path-counting argument.

We develop a method for deriving Gaussian optimality results for bosonic quantum systems from inequalities for qubit systems. Inspired by Gross's derivation of the Gaussian logarithmic Sobolev inequality from an inequality on the two-point space, we use qubits as quantum two-point spaces and lift bosonic Weyl operators to pseudo-Weyl operators on large qubit systems. By controlling weighted norms and relative entropy in the fluctuation limit, we establish two transfer theorems that convert tensorized qubit inequalities into inequalities for bosonic Gaussian channels. As a first application, we prove that the sharp $2$-logarithmic Sobolev inequality for the bosonic Ornstein--Uhlenbeck semigroup tensorizes without loss in the constant. We also establish a sharp output entropy inequality for tensor powers of a class of qubit channels. This includes a quantum Mrs.~Gerber's lemma determining the minimum output entropy of tensor powers of the qubit depolarizing channel at fixed input entropy. Applying our relative entropy transfer theorem, we obtain multimode constrained minimum output entropy bounds for Gaussian additive-noise channels and thermal attenuators in the heating range.

We design and optimize a quantum error correction (QEC) decoder for NVIDIA GPUs, combining Relay belief propagation, a state-of-the-art message-passing algorithm, with order-zero ordered statistics post-processing. Our implementation uses CUDA Graphs to control GPU execution, stops updates for converged samples, and collects unresolved samples in queues for post-processing. We optimize sparse traversal through coalesced message accesses, prefetching, and register reuse, and accelerate binary post-processing with warp-level collectives. In addition, mixed FP16-FP32 arithmetic and INT8 quantization reduce message storage and traffic while retaining accuracy using accumulators at higher precision. We evaluate surface, hypergraph product, and bivariate bicycle code workloads on NVIDIA A100 and GH200 data-center GPUs and a commodity RTX 5080. On the bivariate bicycle code at error probability 0.003, INT8 halves amortized decoding time relative to independently tuned FP32 with a negligible logical error rate increase on RTX 5080. With independent syndrome batches submitted back-to-back to concurrent decoder instances, RTX 5080 delivers 91% of GH200's highest measured throughput with an 8.9x shorter median submission-to-correction latency. The combination of performance optimization, mixed precision, INT8 quantization, and concurrent decoder instances opens a path toward QEC decoder clusters built from commodity GPUs.

Gradient-based algorithms are often applied to identify an optimal control for maximizing a quantum objective functional by following a steepest ascent path to the top of the control landscape. In contrast, this paper explores straight shots through control space where movement along such a path corresponds to a less demanding monotonic complete climb up the landscape for the optimal objective value. Existing studies of control landscapes have revealed the presence of straight shots, but identifying them required computationally intensive stochastic methods. In this paper, we introduce a non-stochastic straight-shot search algorithm (STSA) that identifies a large class of straight shots. We apply STSA to numerically generate more than 10,000 distinct straight-shot optimization paths and analyze their statistical distribution for each of the objectives of (i) state-to-state transitions, (ii) general observables, and (iii) unitary transformation generation. The results show a decrease in the nearest-neighbor distances among straight shots as the sample size increases, suggesting their prevalence in control space. We further conjecture that the starting locations of the straight-shot pathways on a landscape level set may form connected neighborhoods, motivating future investigation into their underlying topological structure. The present paper focuses on the use of STSA for locating massive numbers of straight solutions. However, the STSA is not a high-efficiency algorithm in its present form, but the discovered prevalence of control straight shots leaves open future advances to accelerate the discovery of straight shots as optimal controls.

Systems with flat bands are interesting as they potentially host many exotic quantum phenomena that would be hard to observe in usual systems with dispersive bands. Multiple approaches were developed to construct flat band systems, with most of them requiring fine-tuning and/or solving a challenging inverse-eigenvalue problem. In this article we work with an idea that uses a parent bipartite system to generate a family of flat bands by means of Hilbert space projections. This method is largely free from fine-tuning constraints and allows us to identify conditions for a Hamiltonian to guarantee flat bands at desired energies, with desired degree of degeneracy. We also show that one can control the touching points of the flat band with dispersive bands at any desirable point in the Brillouin zone. In the process, we identify perturbations that preserve the flat bands or split them controllably. This approach provides easy tunability in designing flat band systems with desired properties.

The article outlines key topics related to deriving kinetic equations and, in general, to the relationship between the evolution equations governing quantum many-particle systems. The main issues being considered are the mathematical origin of quantum kinetic equations, novel methods for deriving kinetic equations from hierarchies of evolution equations for quantum systems, specifically focusing on kinetics within the framework of the evolution of observables, and the generalization of the quantum kinetic equation specified by non-separable initial states.

Performant classical tools for simulating quantum circuits are important for benchmarking and supporting upcoming quantum devices. Pauli propagation offers promising capabilities, but deep circuits usually cause a rapid growth in the number of Pauli strings and can quickly exhaust the available memory. In this work, we introduce a randomized protocol that combines a specialized resampling schedule, merging, and a controlled amount of bias to keep the propagating Pauli sum within any prescribed memory budget. Additional computational resources can then be spent on embarrassingly parallel repetitions that systematically improve the estimate. Building on the open-source library PauliPropagation.jl, we show that 1) increasing memory of each simulation reduces the error systematically more than outside averaging, 2) resampling just enough to apply the next gate delays variance accumulation and gives better error-per-time trade-offs than more aggressive resampling, and 3) a small, controlled bias is crucial in cutting down variance and pushing far beyond unbiased randomization. The resulting framework can reproduce deterministic calculations while requiring several orders of magnitude less memory.

Determining the symmetry of the Cooper pairing in superconductors is a central challenge in condensed matter physics. Time-reversal symmetry breaking (TRSB) is among the most distinctive symmetry-breaking pattern of a superconductor. An important subset of TRSB pairing states, including the topological $p_x+ip_y$ pairing, is expected to exhibit the optical anomalous Hall effect. However, the microscopic ingredients that enable the Hall response and their underlying organizing principle in clean superconductors remain unelucidated. Here, we develop a unified theory for TRSB multiband superconductors possessing inversion symmetry, and establish their intrinsic optical Hall response as fundamentally a quantum-geometric phenomenon. We distinguish unitary and nonunitary TRSB states. Diagrammatically, we identify two classes of processes: single-electron tunneling and Cooper-pair tunneling. Both involve at least one interband tunneling event driven by the interband velocity-which is closely tied to the interband Berry connection. We rigorously prove that interband pairing is a prerequisite for unitary states to generate intrinsic Hall response, whereas it is not absolutely needed for nonunitary states. In nonunitary states with intraband pairing alone, the Hall effect can arise through single-electron tunneling, provided spin-orbit coupling is present. An effective theory obtained by integrating out the hole degrees of freedom reproduces these results and shows how pairing may endow electrons with effective Berry curvature. Finally, through symmetry analysis, we show that intrinsic resonances near the superconducting gap edge are allowed in nonunitary states but forbidden in unitary states. Our work thus establishes quantum geometry as a unifying principle for the intrinsic Hall response in superconductors and provides a guide for distinguishing different candidate TRSB pairings.

Double-layer systems with narrow or flat electronic bands may exhibit spontaneous interlayer coherence, described by a layer-pseudospin ferromagnetic order parameter. In modern realizations of layer-pseudospin ferromagnets, the electrons carry additional valley degeneracies, endowing each layer with a valley-pseudospin degree of freedom. We study their nonequilibrium steady states driven by a static interlayer voltage bias in the presence of interlayer tunneling. While in the low-bias regime, the system is in a static state with parallel valley pseudospins between the two layers, we show that in the high-bias regime, the dynamical precession of the layer-pseudospin stabilizes the valley pseudospins in the antiparallel configuration, strongly suppressing the interlayer tunneling. This dynamical tunneling blockade leads to an absence of ac current and a sharp drop of the dc tunneling current to a tiny value, in stark contrast to conventional quantum Hall double layers.

One of the major challenges of modern foundational physics is the combination of quantum physics and general relativity into a theory of quantum gravity. A severe obstacle are the required extremely high energy scales for direct tests of quantum gravity effects. In recent years, attention has shifted towards near-future experimental predictions of effective or phenomenological models, such as gravitationally induced entanglement or interactions of linearized gravity with non-relativistic measurement devices. These developments motivate us to study the coupling between the quantized metric perturbation and an anisotropic quantum rigid rotor. The intuitive motivation for our study is that a sufficiently heavy rotor consists of a very large number of component systems. Although quantum gravitational effects are completely negligible at the scale of a single atom or molecule, the effects can get amplified by the sheer number of constituents. The resulting effective model describes the gravitational analogue of the angulon quasiparticle excitations discussed in condensed matter physics, suggesting a pathway for future analogue experiments. As a first concrete test of our model, we derive the gravitational Lamb shift for the energy eigenstates of the rotor, which become dressed by a cloud of virtual gravitons. Although the effect is very small, it could provide a concrete test for whether gravity is truly quantum.

Kerr-cat qubits offer a hardware-efficient route to fault-tolerant quantum computing by suppressing bit-flip errors exponentially, while phase-flip errors increase only linearly with the mean photon number. To maintain this protection, entangling operations must be bias-preserving, ensuring that phase-flip errors occurring during the gate do not propagate into bit-flip errors. In this paper, we propose an asymmetrically threaded SQUID (ATS) parametric coupler to implement high-fidelity, bias-preserving entangling gates between Kerr-cat qubits. By engineering a photon-number asymmetry between the control and target modes, we enable fast gate operations that suppress non-adiabatic leakage without complex pulse shaping. Through numerical simulations of the full circuit Hamiltonian, we demonstrate a bias-preserving CX gate achieving 99.69% fidelity in the absence of photon loss for a gate duration of 50 ns. Under a single-photon loss rate of 100 kHz, our protocol yields a noise bias of 9922, exceeding the noise bias of a naive non-bias-preserving CX implementation by approximately a factor of 570. These results support the ATS coupler as a valuable building block for concatenated cat-qubit architectures.

Fault-tolerant quantum computers need fast and accurate error decoding. We present CoDecoder, a small neural frontend that composes with an existing decoder to improve accuracy and reduce mean decoding time. It predicts each shot's logical outcome, retains confident predictions and routes the remaining shots to the unchanged fallback. A logical-operator-aware output head scores shifted logical operators, combining equivalent logical lines on surface codes and deciding logical qubits jointly on bivariate-bicycle (BB) codes. Fused GPU inference and efficient routing reduce the overhead paid on every shot. In registered tests under circuit-level noise, composition reduces failures by 6.4-31.4% relative to correlated matching on surface codes of distance 7-17 and by 22-50% relative to full-DEM Relay-BP on two BB codes, with 2.3-124-fold speed-ups across these comparisons. With our re-implementations of the neural decoder Cascade, composition reduces decoding time in all four settings. A joint decision of both decoders on the routed shots keeps this speed and makes the composition more accurate than Cascade in all four, with 14-18% fewer failures on the [[72,12,6]] code. On the [[72,12,6]] BB code, a conventional head with independent logical outputs fails 3.8-5.0 times as often as our joint class score under matched training conditions. Per-shot analysis shows how composition gains accuracy. On retained shots, the frontend corrects more fallback errors than it introduces, even when it is less accurate overall.

Calderbank--Shor--Steane (CSS) codes support decoding and fault-tolerant logical operations through separate pure $X$ and pure $Z$ stabilizer checks. Generator choices and single-qubit Clifford transformations can obscure this structure. We give a deterministic polynomial-time algorithm that decides whether an arbitrary stabilizer code is locally Clifford-equivalent to a CSS code and constructs the required transformation and CSS checks whenever such a form exists. For $m$ possibly redundant generator rows on $n$ qubits, the algorithm uses $O(mn^2+n^4)$ binary field operations. We reduce the problem to affine linear systems by characterizing local projectors that preserve the span of the binary stabilizer labels. The conversion preserves code parameters and check sparsity for quantum low-density parity-check (qLDPC) codes. We demonstrate CSS recovery and decoder reuse and resolve previously open LC-to-CSS classification questions for published code constructions. For graph states, LC-to-CSS equivalence corresponds to the existence of a bipartite graph in the local-complementation orbit. We derive a necessary-and-sufficient adjacency-matrix criterion for this property and construct such a graph whenever one exists. Our algorithm makes CSS decoding and fault-tolerant constructions accessible throughout the local Clifford equivalence classes of CSS codes.

We formulate quantum reference frames within the Dirac quantization of gauge theories, where physical states are obtained from a kinematical Hilbert space $\mathcal{H}_{\rm kin}$ by group averaging. We assume the gauge group $G$ is unimodular, and we define a quantum reference frame as a system of coherent states associated with a group $G_R$ of frame orientations acting on a tensor factor of $\mathcal{H}_{\rm kin}$. In direct analogy with the Faddeev-Popov procedure in path integrals, we show that the physical inner product can be written in terms of a choice of frame orientation with an appropriate operator measure, but that the physical Hilbert space is independent of this choice of frame. This yields a generalization of the Page-Wootters reduction map used to define conditional states and conditional probabilities of measurement outcomes given a frame orientation. These probabilities correspond to the expectation values of relational Dirac observables obtained from generalizations of previously considered relativization maps. Our main result is that the map that implements a change of frame is unitary, even when $G$ does not act as a tensor-product representation across a factorization of $\mathcal{H}_{\rm kin}$. The formalism therefore accommodates interactions between reference frames and the systems described relative to them. We apply this formalism to temporal frames, showing that a unitary Schrödinger equation emerges for an interacting clock and system, and that a previously reported time-nonlocal Schrödinger equation is recovered in an appropriate limit. With this, problems of non-unitarity are avoided by the use of the gauge-fixing measure in the physical inner product. We also discuss the case of interacting spatial frames, where the known correspondence between coherence in one frame and entanglement in another is shown to depend on the coupling.

Separately amplifying gate, latency, and mid-circuit measurement errors can simplify zero-noise extrapolation, but a weak interaction between amplification knobs does not establish an accurate zero-noise limit. We distinguish observable separability, response-model adequacy, and calibration of that limit, and test them in a pre-specified $2^3$ factorial experiment on three IBM dynamic circuits. For the primary echoed spectator observable, the latency-measurement coefficient is $b_{LM}=+0.0007$ with a nominal 95% bootstrap interval $[-0.0033,+0.0049]$. A separately planned follow-up meets a $\pm0.005$ equivalence criterion and recovers two injected interactions; both repeat runs nevertheless trigger the drift rule. Multi-knob extrapolations have smaller median absolute errors than the single-knob comparisons, yet all five original strategies exclude the known ideal value for three of six observables. Duration controls support a model-dependent contribution to the spectator deficit from unequal decay rates in native padding and added delay. We give an explicit construction showing why measurements at two measurement-knob levels cannot identify the extrapolated limit without response assumptions. A post-hoc precision analysis and an additive full-factorial estimator expose a further bias-variance trade-off hidden by point-error comparisons. The experiment provides a diagnostic of the implemented response surface, not a certification of physical channel independence or mitigation accuracy.

Motivated by a recent experimental work $[\href{https://arxiv.org/abs/2608.20327}{\text{arXiv:}2608.20327}]$, we theoretically investigate the nature of phase transitions in a trapped dipolar quantum gas upon tuning the contact interaction strength and dipole orientation. Using extended Gross-Pitaevskii simulations including thermal and quantum effects, we map the phase diagram comprising unmodulated superfluids, triangular droplet arrays, and stripe states. We further characterize the order of the transitions separating them through imaginary-time hysteresis analysis. The unmodulated-to-modulated transition evolves from discontinuous to continuous with increasing dipole tilt before becoming discontinuous again at large tilts. The degree of continuity is further affected by particle number, temperature, and confinement. While continuous behavior generally correlates with the emergence of stripe states, this correspondence is not systematic, and finite-size effects also influence the continuity of the transition. The triangular-to-stripe transition is found to be discontinuous at small contact interaction strengths and becomes increasingly continuous upon approaching the unmodulated-to-modulated phase boundary. Our results reveal a tunable transition order in finite dipolar quantum gases and provide guidance for its experimental investigation.

Quantum batteries can outperform their classical counterparts through collective quantum effects, yet the conditions enabling such advantage remain unclear. Using a generic class of free-fermionic chargers we prove that global operators are insufficient for scalable superextensive charging and that a cumulative hierarchy of many-body operators is required, with the structure of the battery determining the degree of advantage. This is obtained by relating the charging power to the norm of the commutator between the battery and charger Hamiltonians and deriving an upper bound only capturing noncommuting terms. Moreover, we revisit the concept of participation number and propose an effective definition that accounts for the relative strength of the contributing terms, correlating it with the charging power scaling. Not limited to quadratic Hamiltonians, our results establish cumulative locality as a key resource for quantum charging advantage.

We prove a complete modified logarithmic Sobolev inequality with a system-size-independent constant for Chen--Kastoryano--Gilyén Gibbs samplers on one-dimensional spin chain at every fixed positive temperature. The result holds for Hamiltonians with bounded finite-range interactions, including noncommuting and spatially nonuniform interactions. It yields trace and diamond mixing times of order $O(\log N+\log(1/ε))$. The proof establishes complete spatial entropy factorization and absorbs quasi-local errors as conditional relative entropy at the original joint state and reference. The static estimate also yields a system-size-independent CMLSI for the single-site Petz heat-bath and regularised heat-bath dynamics.

We study the minimum persistent memory required to distribute a graph state through a quantum switch. Specifically, consider a central switch that assists $n$ remote users in distributing a graph state, using independently generated user-switch Bell pairs. Since Bell-pair generation is probabilistic, different links generally succeed at different times. When a Bell-pair is generated, the qubits may need to be stored in memory while waiting for other links to succeed. Recently, new protocols have been proposed to reduce this storage overhead by processing and releasing some switch qubits before all Bell links are available. However, these protocols do not characterize the minimum persistent switch memory required at each stage. Moreover, the local-cover method in the state-of-the-art Piecemaker protocol is computationally expensive for general target graphs. In this work, we characterize the minimum persistent switch memory required after any subset of users' Bell links are generated and processed. We then develop an online stabilizer-transition protocol that attains this limit, which can be implemented in polynomial time in the number of qubits $n$. Remarkably, this optimal protocol can provide substantial memory reductions over existing heuristic approaches. In particular, for the path graph $P_n$ over $n$ users, Piecemaker protocol requires at least $\lfloor n/2\rfloor$ qubits of peak persistent memory for \textit{every Bell-links generation order}, whereas under the order $(1,2,\ldots,n)$, our protocol requires only one persistent switch qubit. Finally, the same stabilizer-transition framework also provides a direct forward construction for sequential graph-state generation using the minimum number of quantum emitters, equal to the maximum of the height function.

Quantum low-density parity-check codes now reach encoding rates up to 50% at useful distances. Their checks however are long-range group actions, not local neighbourhoods, and that connectivity has so far been supplied by neutral atoms. Silicon spin qubits offer the same primitive --- coherent transport of qubit blocks --- through electron shuttling, and on microsecond rather than millisecond timescales. They however travel along fabricated tracks rather than free space: permutations an atom array obtains by moving tweezers must here become collision-free motions on a physical lattice. We here present the first code and spin-qubit hardware co-design. We build an architecture whose geometry mimics that of a family of non-abelian groups, broad enough to host codes of excellent parameters: a hierarchy of nested conveyor-belt loops on a plain square lattice of shuttling tracks, in which every group multiplication becomes a rigid, globally controlled motion of whole qubit trains. We call it NeST, for Nested Shuttling Tracks. A code search over the family returns rate-20% mitten codes up to $[[1400,280,\leq 28]]$, and circuit-level simulations including shuttling dephasing give thresholds above $10^{-3}$ with sub-$50μ$s stabiliser cycles, two to three orders of magnitude faster than neutral-atom implementations. Via extrapolations, we estimate that this largest code may reach a logical error probability per qubit per round of $10^{-14}$, assuming a ten-fold improvement on early shuttling demonstrations, with other physical errors at p=0.1%. Logic is compatible with NeST too: for the [[150,30,10]] code we build a code-surgery gadget in which every qubit again moves only by rigid belt motions, at no qubit cost and a 29% increase in gate layers. This demonstrates that ultra-low-overhead fault tolerance and a fast clock speed are not competing goals, and that silicon spin qubits can supply both.

We demonstrate a hybrid quantum-classical approach for exploring ground-state manifolds of maximum independent set problems, in which quantum hardware supplies the initial solutions and an entirely classical post-processing algorithm expands them, increasing the solution diversity of quantum hardware measurements by up to several orders of magnitude. Quantum optimization devices, while capable of generating high-quality solutions, can suffer from fundamental sampling limitations. This is particularly problematic for applications that strongly depend on a large variety of uncorrelated optimal solutions. We apply the Houdayer cluster update algorithm to systematically expand quantum-generated solution sets through classical post-processing. We validate our approach on a test bed of 43 problem instances from QuEra's Aquila analog annealing device, achieving diversity amplification factors, defined as the increase in the number of distinct solutions at a given set size, of up to 11923x with a median of 24.3x across different problem scales and hardness parameters. Because exact ground-state degeneracies are known for these instances, the recovered fraction of the manifold can be measured rather than bounded: post-processing recovers a median of 21% of the ground-state manifold, and provably all of it for six instances. We also demonstrate that, in some cases, the classical post-processing can discover independent sets larger than those found by the quantum hardware, thus improving on solution quality and not just diversity. While the method is non-ergodic and cannot guarantee complete manifold coverage, it consistently discovers a larger number of high-quality, and in some cases strictly better, configurations than quantum sampling alone. This work demonstrates how simple classical post-processing can enhance the utility of quantum optimization results.

Long-range interactions in many-body quantum systems give rise to a wide range of dynamical phenomena, from collective dynamics well described by integrable mean-field models with symmetric all-to-all couplings, to fast scrambling of quantum information from disordered long-range interactions. Here, we investigate scenarios in which both regimes emerge within a single deterministic, translation-invariant XY spin model with long-range couplings. We consider a sparse powers-of-two (PWR2) graph, where each spin interacts with a logarithmic number of neighbors, and a power-law-decaying model. By altering the initial state via local perturbations on a completely symmetric state, we show that the dynamics changes from collective to scrambling as witnessed by bipartite and multipartite entanglement measures. We characterize this collective-to-scrambling crossover using Lyapunov exponents in the semiclassical regime, and show that the spectral properties of the coupling graph adjacency matrix provide a very efficient tool to predict the onset of fast scrambling. Our results offer a unified framework for controlling the switch between collective and scrambling dynamics in a setup accessible in experiments with neutral atoms in cavities or in tweezer arrays.

Trapped-ion, neutral-atom, and circuit QED quantum computers naturally enable coupled qubit-boson simulations. Boson-fermion interactions arise in quantum field theory, where renormalization is required to obtain finite results. We study one of the simplest examples of a coupled fermion-boson system, the static Yukawa model, on the QSCOUT trapped-ion system. We use similarity renormalization to express the same physics in terms of effective particles described by different values of the renormalization parameter $s$. This enables us to map data taken in the window of bosonic occupancy that is experimentally accessible to larger occupancies of distinct effective particles. We use this to study strongly coupled, high-occupancy regimes despite limited readout ranges. Using a trapped-ion qubit-boson device on Sandia National Laboratories' QSCOUT platform, we demonstrate the time evolution of the static Yukawa model.

We evaluate the electron scattering properties in CoSi thin films having either twin (heterochiral) or non-twin (homochiral) grain boundaries using first-principles quantum transport calculations. We find that scattering across a twin grain boundary is more resistive than scattering across a non-twin grain boundary and that non-twin grain boundaries have a greater percentage of surface conduction than twin grain boundaries. This is corroborated by the transmission eigenstate profiles, which show that the surface Fermi-arc electrons can transmit past the non-twin grain boundaries between homochiral domains on the same surface without significant backscattering. In contrast, these surface electrons get scattered along the twin grain boundaries between heterochiral domains to the opposite surface, resulting in partial forward transmission and partial backscattering that yields higher grain-boundary resistivity. This work helps elucidate the complexities of electron transport in chiral topological semimetals for potential application in next-generation nano-interconnects.

Identifying the quantum signatures of classical chaos remains a central question in quantum physics, and quantum scrambling provides a new perspective on this correspondence. We study two distinct limits of the same model to examine how the correspondence between chaos and scrambling changes across different regimes. The thermodynamic-limit anisotropic Dicke model exhibits a close correspondence between chaos and scrambling, whereas this correspondence breaks down in the large-frequency-ratio limit of the anisotropic Rabi model (ARM). The contrasting chaotic behavior in the two limits originates from the different numbers of classical degrees of freedom, whereas their similar scrambling behavior stems from eigenstate delocalization. This implies that, in the large-frequency-ratio limit, eigenstate delocalization alone is insufficient to qualify the ARM as a classically chaotic model. This finding suggests that identifying chaos in quantum systems requires jointly considering the classical degrees of freedom and eigenstate delocalization.

Early studies on the Dicke model linked superradiance to quantum chaos, whereas later anisotropic Dicke and Rabi studies reached apparently conflicting conclusions. We resolve this tension by distinguishing global chaos from local instability. Along the isotropic Dicke path, a sweep at fixed low excitation energy crosses both the superradiant boundary and a nearby chaotic window, explaining the reported correlation. However, the anisotropic Dicke model can be chaotic in the normal phase and regular in the superradiant phase, making superradiance neither necessary nor sufficient for global chaos. A fidelity out-of-time-order correlator (FOTOC), in contrast, probes the local stability of the stationary point selected by the initial wave packet. The superradiant transition destabilizes the origin, whereas a change in anisotropy can restore its stability and create displaced saddles. Wave packets centered at these saddles exhibit exponential FOTOC growth even on a classically regular Dicke energy shell with Poisson statistics. This local sensitivity also enables quantitative spectroscopy: combined with the topology of stationary points and local density of states relations, FOTOC dynamics reconstructs the absolute amplitudes of spectral singularities in both models without fitting the density of states.

We present a fully quantum formulation of the spinterface model for the chirality-induced spin selectivity (CISS) effect, implemented within the non-equilibrium Green's function (NEGF) formalism. The model consists of a gold atom hosting a localised magnetic moment, coupled to a chiral molecular chain with Rashba spin-orbit coupling, and contacted by two non-magnetic leads. The magnetic moment is determined self-consistently from the non-equilibrium electronic distribution, and the spin-resolved transmission is computed from the mean-field Hamiltonian. We show that the interfacial magnetic moment and the chiral Rashba term cooperate to produce large current polarisations that reproduce the key experimental signatures of CISS: high polarisation, a threshold emergence at four total sites followed by interference-modulated growth with chain length, thermal suppression, and sign reversal upon chirality inversion. The central new result of this work is a clean separation of the CISS effect into an even (achiral) and an odd (chiral) contribution to the spin current, $I_{S_z}(φ) = I_{S_z}^{\rm even}(φ) + I_{S_z}^{\rm odd}(φ)$. We demonstrate that $I_{S_z}^{\rm odd}$ vanishes exactly at fixed $m_z$ for chains of fewer than four sites and becomes non-zero for chains of four or more sites, with the smallest junction exhibiting a non-zero odd part being the four-site geometry (one gold atom plus three molecular sites). The odd part arises from reciprocity breaking in a device that is simultaneously chiral, magnetically asymmetric (moment on the gold end only), and long enough to support two or more Rashba-active bonds. This provides a direct, parameter-free test of whether an observed spin signal is genuinely chiral or arises from an achiral spin-valve mechanism.

Structured light provides a route to controlling quantum materials not only through its polarization, but also through its spatial profile and orbital angular momentum (OAM). We develop real space theories of a Weyl semimetal driven by a vortex beam and show that optical OAM generates highly localized Floquet vortex states with pronounced circulating photocurrents. Exploiting cylindrical symmetry, we derive a Bogoliubov-de Gennes-like radial equation that resolves the states by angular momentum and reveals their evolution between the light-dressed Weyl cones. For Laguerre-Gaussian beams, the spatially varying drive produces strong hybridization between localized vortex states and bulk states. We complement this continuum description with a Wilson-lattice formulation that retains the full two-dimensional spatial structure and enables direct calculation of local photocurrents. Both approaches consistently identify OAM-induced vortex states localized around the beam axis. The lattice calculation further shows that these states support substantially stronger circulating current densities than the more extended surface states, with the largest current densities associated with the most strongly localized, low-angular-momentum vortex modes. Our results establish optical OAM as a tunable control parameter for creating and manipulating localized current-carrying states in Weyl systems and provide a real-space framework for studying photocurrents generated by spatially structured light.

Phase transitions (PTs) in quantum many-body systems offer a powerful route to manipulate the performance of quantum batteries (QBs). Here, we investigate an anisotropic Dicke QB with Kerr nonlinearity, focusing on the role of PTs in the charging process of the QB system. By analyzing how the Kerr nonlinearity reshapes the cavity level-spacing structure, we find that multiple near-degeneracies emerge at specific nonlinearity strengths. Away from the region of multiple near-degeneracies, the stable stored energy is governed primarily by the ergodic-nonergodic transition (ENET), whereas within this region it is controlled by first- and second-order dissipative phase transitions (DPTs). We employ Liouvillian spectral theory to quantify the critical slowing down associated with the DPTs, and use the Wigner function to characterize the properties of the cavity field in the vicinity of criticality. We optimize the charging process via reinforcement learning (RL) and reveal the physical mechanism underlying performance enhancement from the perspective of ergodic and nonergodic phase dynamics. Our results offer a feasible pathway for manipulating and optimizing quantum battery performance based on intrinsic PT behaviors.

We give a bounded-error quantum polynomial-time algorithm for finding hidden parabolic subgroups of $\mathrm{GL}_n(R)$ over any effectively presented finite chain ring $R$. We call auxiliary group elements or subgroups used to extract information through oracle queries \emph{probes}. For chain length at least two, elementary abelian socle probes first recover the complete flag modulo the maximal ideal. When the residue field has size $q\ge3$, we reconstruct the flag recursively, lifting rank-one terminal members one digit at a time. The intermediate digits reduce to abelian hidden subgroup problems, while the final digit is a finite-field multiple-shift problem solved using learning from subset and Fourier sampling. For $q=2$, where distinct flags can have the same stabilizer, we instead lift the conjugate parabolic subgroup through the congruence filtration. A final linear system determines it modulo normalizer directions. The algorithm outputs generators with probability at least $1-ε$ in time $\mathrm{poly}(n,\log|R|,\log(1/ε))$. Consequences include $\mathrm{GL}_n(\mathbb{Z}/N\mathbb{Z})$ for every $N\ge2$ and, with an explicit maximal-order presentation, $\mathrm{GL}_n(\mathcal{O_K}/N\mathcal{O_K})$ for number fields $K$.

We advance the compact dressed Hamiltonian (CDH) framework to simulate the dynamics of open quantum systems strongly coupled to structured bosonic environments. The CDH approach combines reaction-coordinate mapping with a polaron transformation, incorporating strong system-environment hybridization into a dressed representation before truncating the collective bosonic mode. As a result of this truncation, dynamical features are captured with substantially fewer states than in the original representation. The residual environment is treated using a weak-coupling Markovian quantum master equation. We benchmark the method for spin-boson-type models including a single spin, coupled spins, and spin ensembles, considering both resonant and off-resonant regimes and weak to strong system-bath coupling. Comparisons with hierarchical equations of motion and converged reaction-coordinate calculations demonstrate that the CDH representation systematically approaches the reference dynamics with a compact Hilbert space, accurately reproducing oscillation frequencies, relaxation behavior, and long-time populations over a broad parameter regime. The method further captures cooperative phenomena, including bath-mediated interactions, synchronization between spins, and signatures for collective emission. Beyond efficient time propagation, the CDH framework provides direct access to the spectrum and eigenmodes of the Liouvillian. We demonstrate that slow dynamical modes converge rapidly in the CDH representation, enabling identification of relaxation timescales without fitting time-dependent observables. As a whole, the CDH framework provides an efficient and physical description of strongly coupled open quantum-system dynamics.

Photonic and qubit-based (digital) approaches to quantum computing are largely regarded as separate paradigms. This article aims to bridge these paradigms by developing a method for mapping quantum-optical systems onto qubit-based quantum circuits. The key ingredient enabling this mapping is the introduction of a truncation of the Fock space describing single-mode optical states. Within this framework, representations of basic photonic operations are developed, including the phase-rotation operator, the displacement operator, the squeezing operator, and the beam splitter. Explicit quantum circuit constructions are provided for Fock-space truncations of dimension $N=2$ and $N=4$. We discuss benchmarking of the implemented operations and identify the regime of applicability and the limitations of the proposed method. The presented results can be used to simulate quantum optical circuits on qubit-based quantum computers, with special relevance to Gaussian Boson Sampling in the low-photon-number regime. To demonstrate the practical applicability of this approach, we complement the theoretical framework with a Python-based quantum programming tool CO$Φ$ that compiles Blackbird quantum-optics programs into qubit-based OpenQASM circuits using a truncated Fock-space encoding. The compiler is available on GitHub at https://github.com/Quantum-Cosmos-Lab/cophi.

Cloud-accessible quantum computing has made heterogeneous Quantum Processing Units (QPUs) available through provider platforms that differ in qubit technology, calibration state, queueing behavior, and pricing model. This heterogeneity makes execution management a quantum-engineering concern: a quantum circuit may be executable on several backends, but the resulting cost, latency, fidelity, and reproducibility depend on backend selection and on how measurement shots are allocated. This paper presents the Quantum Broker, an open-source and provider-agnostic framework for Quality-of-Service-aware quantum execution management. The framework operationalizes shot-wise distribution by exploiting the statistical independence of quantum measurement shots to dispatch a single circuit across multiple heterogeneous QPUs according to user-defined constraints and optimization objectives. It combines a modular execution architecture, interchangeable backend-profiling strategies, and the Quantum QoS Specification Language (QQSpec), a declarative language for expressing QoS requirements. Dispatch planning is supported by two solver backends: a mixed-integer linear-programming (MILP) solver, and a nonlinear dual-annealing solver. Experiments on benchmark quantum circuits and noisy simulator backends show that the Quantum Broker can produce feasible QoS-aware dispatch plans under heterogeneous backend conditions and can improve QoS satisfaction with respect to single-backend and naive multi-backend baselines. The results also expose a practical trade-off between planning time and dispatch quality, with the nonlinear solver producing higher-quality allocations at increased computational cost. Overall, the Quantum Broker provides an extensible execution-management layer for engineering portable, reproducible, and QoS-aware quantum software over fragmented quantum cloud infrastructures.

Clean, interacting, periodically driven systems are believed to thermalize to featureless, infinite-temperature states that preclude the formation of stable ordered states. Here, we show stable quantum order, distinct from prethermal order, and its phase transitions in the ground state of the average-energy operator. Decomposing the time evolution into geometric and average-energy dynamics, we apply Geometric Floquet theory to identify the Floquet ground state. We derive a general variational principle to compute the Floquet ground state in large interacting periodically driven systems, and use it to develop a matrix product state algorithm. In driven nonintegrable chains of more than 100 interacting spins, our numerical simulations exhibit a gapped, area-law entangled Floquet ground state in extended parameter regimes; the ground-state manifold can support both dressed equilibrium order (e.g., Floquet antiferromagnets) and inherently nonequilibrium order (e.g., ground-state time crystals). This quantum order is protected by a finite average-energy gap, which closes at phase transition points upon changing model parameters. We decompose Floquet phases of matter into their equilibrium and nonequilibrium elements: whereas the Floquet ground state at any fixed time is a representative of an equilibrium phase of matter, the nonequilibrium content is entirely produced by the drive holonomy and is geometric. Finally, we identify quasilocal counterdiabatic driving as a mechanism for the stability against heating of gapped Floquet ground states in nonintegrable quantum systems, and argue why Floquet ground states evade the Eigenstate Thermalization Hypothesis. Our work enables the study of interacting nonequilibrium matter deep into the many-body regime, and lays the foundations for the engineering of strongly correlated ordered quantum states.

The resource theory of coherence quantifies the quantum properties of states and their role in quantum information processing. Extending coherence theory to ensembles, the natural objects in quantum communication, remains an active research direction, with their operational potential still being explored. In this work, we establish a maximally coherent ensemble in every finite dimension: the continuous ensemble of pure states distributed according to the normalized Haar measure attains the tight upper bound on basis-free relative entropy ensemble coherence. We then prove that ensemble coherence bounds the effective informational advantage of postselective measurements over the Holevo quantity for two equiprobable pure states. Finally, for the qubit B92 QKD protocol, we show that the coherence of Alice's ensemble upper-bounds the secret key rate in the asymptotic regime. These results give ensemble coherence a quantitative operational meaning in quantum communication and cryptography

We theoretically investigate electronic driving of a torsional mode in a suspended carbon nanotube quantum dot. The valley states in a nanotube carry opposite orbital magnetic moments along the tube axis, and intervalley mixing forms valley-mixed eigenstates whose splitting can be controlled by an axial magnetic field. We formulate an orbital-rotation coupling between the torsional angular velocity and the valley orbital angular momentum. Using a master equation for sequential tunneling through normal-metal electrodes, we calculate the steady-state current and the phonon distribution of the torsional mode. When the valley-state splitting matches the torsional phonon energy, orbital transitions can drive the mode out of equilibrium. The contacts control both phonon pumping and its electrical readout, allowing substantial excitation with a positive, vanishing, or negative current response. The mechanism requires no intrinsic spin or valley polarization of the electrodes, but uses state-dependent tunneling at the contacts.

When an ensemble of emitters is confined within an optical wavelength, its radiation can become correlated, leading to cooperative emission. In two-dimensional (2D) transition metal dichalcogenide (TMD) electron-hole bilayers, strong light-matter coupling enables the formation of interlayer excitons (IXs), long-lived dipolar excitations that provide an ideal setting for emergent collective phenomena. Here, we engineer an atomically thin light-emitting diode (LED) that generates electroluminescence (EL) from electrically injected IXs that are confined near the sample edges by an edge-enhanced fringing electric field. By measuring Hanbury-Brown-Twiss photon-photon correlations, we find pronounced signatures of collective decay in the form of large photon bunching followed by finite delay antibunching and bunching revivals. These emitter correlation signatures disappear when free charge carriers are doped to form a degenerate Fermi sea but are enhanced by the introduction of localized electrons. The results are consistent with a many-body quantum master equation that models the steady-state superradiant photon statistics of incoherently injected IXs. Our work establishes steady-state cooperative emission in a 2D TMD LED as a platform for studying strong light-matter interactions in electrically driven, non-equilibrium phases of Bose-Fermi mixtures.

We investigate the dynamics of two bosons in a tilted one-dimensional optical lattice with both standard and density-assisted tunnelling. The relative sign of the two tunnelling processes strongly affects the Bloch dynamics, leading to distinct reinforcing and competing regimes. We examine how the tunnelling processes generate correlations and find that, in the absence of onsite interactions, the early-time entanglement growth follows the same scaling with the density-assisted tunnelling amplitude. Finite onsite interaction changes this picture by breaking the symmetry between the reinforcing and competing regimes and enhancing the correlation differently in two regimes. This shows how the interplay between the two tunnelling mechanisms can change dyanmics and entanglement in a controlled few-body setting. Particularly, at equal tunnelling amplitudes, the doublon and singlon sectors decouple completely for arbitrary onsite interaction, lattice tilting, and initial state.

Practical security analysis of Coherent-One-Way (COW) quantum key distribution requires optical-device modeling, finite experimental statistics, and security inference to be treated consistently without conflating assumptions. We present a modular observable-level simulation framework organized through the pipeline θ_phys -> p -> O -> S_j(O), in which physical source, channel, receiver, and detector parameters determine detector-resolved event probabilities, a finite-block layer applies an effective dead-time treatment and generates aggregate detector counts, and interchangeable security evaluators act on the same observable record. The framework is verified against analytical optical, virtual-state, and finite-key relations and evaluated against reported experimental COW-QKD operating points. The Kato finite-key calculation reproduces the refined experimentally reported secure-key rates most closely at intermediate distances, with deviations of -1.5% at 50 km and -10.3% at 75 km. Monitoring bright-port decoy counts agree within 0.9-2.4%, while remaining distance-dependent dark-port residual identifies the principal model-sensitive observable of the present physical description. Applying Kato and Azuma-Hoeffding concentration treatments to identical detector records isolates the effect of finite-key statistical inference and shows substantially tighter Kato phase-error bounds for rare-event monitoring records studied here. Holding the Kato evaluator fixed, joint optimization of coherent-state mean photon number mu and receiver splitting fraction t_B increases model-predicted secure-key rate by 7.4-20.2% relative to optimization of mu alone with t_B = 0.3. The framework therefore provides a common computational interface for experimental reproduction, controlled security-model comparison, model-based protocol optimization, and modular adversarial stress testing in COW-QKD.

We design a hybrid quantum-classical computational workflow, combining density functional theory and dynamical mean-field theory, to investigate the electronic properties of CaCuO2, a parent structure of high-temperature cuprate superconductors. Our approach uses a quantum algorithm as an impurity solver that is based on variational quantum compressed time evolution to compute the time-dependent Greens function on an IBM Heron quantum device. Utilizing error mitigation techniques and a Lehmann representation fitting procedure, we extract the density of states from the signal in the accessible time regime. Despite the significant challenges rooted in the residual imprecision of currently accessible NISQ devices, we successfully resolve the characteristic features of the spectral function. However, we find that the required numerical accuracy for full DMFT self-consistency exceeds current hardware capabilities, indicating that practical real-material DMFT applications will necessitate post-NISQ hardware developments.

Geometric phase gates with addressed laser radiation are widely used in trapped-ion quantum computers to drive high-fidelity entangling gates on an arbitrary qubit pair of a larger ion chain. Such programmable connectivity exploits the collective phonons to mediate the desired interaction, while simultaneously achieving robustness to their thermal fluctuations by a careful calibration of the gate time with respect to the laser and vibrational-mode frequencies. Crosstalk errors can arise when the spectator qubits, which should ideally remain idle during the gate, are partially driven by the laser fields. The minimal crosstalk, which is set by the laser beam size on the spectator ions, can be achieved when the addressing beams propagate perpendicular to the ion chain. However, this results in exciting the radial phonons, and can complicate achieving high-fidelities as the ion chain grows due to the so-called spectral mode crowding. In this work, we present the theoretical description of a scheme recently implemented by Faorlin et $al.$. This scheme overcomes these complications by engineering addressable state-dependent forces along the ion-chain with laser beams that propagate perpendicular to it through the use of structured light gradients. In this way, one can excite the axial phonons and avoid the spectral mode crowding, while simultaneously minimizing the crosstalk. We present a detailed derivation of the entangling gate scheme, together with analytical closed-form expressions for the leading contribution to the gate error caused by thermal motional fluctuations and dephasing noise. Our results confirm that such fluctuations account for up to 93$\%$ of the error budget under the operating conditions of the gate implemented by Faorlin et $al.$. We identify target parameters to reduce the motional error from the reported $10^{-3}$ to the $10^{-5}$ level.

The five-qubit Absolutely Maximally Entangled AME$(5,2)$ state, whose every pair of qubits is maximally mixed so that all its information lives in non-local correlations, could in principle serve as a single shared quantum networking resource for teleporting two unknown qubits in parallel (each via its own Bell measurement and Pauli correction). Nonetheless, its hardware implementations remain scarce despite its theoretical importance. Here, we demonstrate parallel teleportation based on a five-qubit absolutely maximally entangled state, AME$(5,2)$, on the superconducting processor ibm_pittsburgh. We construct three-qubit Clifford decoders that extract two Bell pairs using three logical two-qubit gates for each of 60 inequivalent sender-receiver assignments. Using parallelization and classical Pauli frame post-processing, we retain reference-receiver entanglement on both channels after three teleportation rounds. With XY4 dynamical decoupling and the lowest-cost decoder, the final entanglement fidelities are $0.704\pm0.028$ and $0.680\pm0.022$, where uncertainties are pointwise $99\%$ confidence-interval half-widths over eight trials. Their lower bounds exceed the separability threshold of $1/2$. The decoder with lower circuit depth generally retains higher mean fidelity, and XY4 generally improves on XX. These results establish a hardware demonstration of two-channel entanglement transmission through repeated AME-assisted teleportation and provide compact decoding circuits for reconfigurable multipartite communication.

We review and analyse quantum information-theoretic approaches to black hole evaporation that purport to bring us closer to a resolution of the black hole information paradox. Our focus is on the Page-time paradox and on the contribution of the Hayden-Preskill model to understanding information release under the assumption of unitary evaporation. In this model, the black hole is taken to be a finite-dimensional quantum system whose dynamics can be represented by a quantum circuit, and its information-processing and communication abilities are studied. We identify the assumptions underlying this modelling and highlight two key features, fast scrambling dynamics and entanglement as a resource, that underpin the information release in the model. We argue that this reasoning exemplifies a broader change in how information is used in black hole physics, in which quantum information theory now provides a useful operational modelling framework. This application avoids earlier philosophical objections insofar as it is not based on epistemic ignorance and does not regard information as a substance. This line of reasoning has become central to the debate and, as such, warrants greater attention from the philosophy of physics community.

The quantum marginal problem, concerned with the compatibility of local and global properties of a multipartite quantum system, is arguably one of the fundamental questions in quantum theory. In this article we introduce a novel family of inequalities bounding the allowed local spectra of a pure tripartite state. The number of inequalities in this family grows with the dimension of the system. Most importantly, the inequalities hold for arbitrary dimensions. For equal local dimension at most 4, they generate the complete set of eigenvalue inequalities.

The growing demand for high-capacity, fast-charging, and durable rechargeable batteries has intensified the search for advanced electrode materials, with two-dimensional materials offering large surface-to-mass ratios and short ion-diffusion pathways. Here, pristine and Co-doped Janus HfSSe monolayers were investigated as anode materials for Li-ion and Na-ion batteries using first-principles density functional theory. Pristine HfSSe was found to be dynamically stable and exhibited a 0.85 eV band gap, while Co substitution shifted the Fermi level toward the valence-band region. Adsorption of the first Li or Na layer induced metallic behavior, thereby improving charge transport. Co doping strengthened alkali-metal binding, with the most favorable Li and Na adsorption energies changing from -2.6125 and -1.9800 eV to -3.7405 and -3.0529 eV, respectively. Co doping created electron-deficient sites that enhanced Li/Na binding. Co-doped HfSSe accommodated up to four Li layers and three Na layers, increasing the theoretical capacities from 555.43 to 776.19 mAh/g for Li and from 370.29 to 582.14 mAh/g for Na. The average open-circuit voltages were 0.62 V for Li and 0.29-0.30 V for Na, with minimum migration barriers of 0.2153 and 0.1044 eV, respectively. These results identified Co-doped Janus HfSSe as a promising anode material for Li-ion and Na-ion batteries.

We investigate photon-to-axion-like-particle (ALP) conversion in a finite, linearly polarized laser pulse for a single ALP field with simultaneous scalar-type and pseudoscalar-type couplings to photons. Varying the collision angle between the strong pulse and the probe provides a continuous kinematic scan of the resonant ALP mass. For fixed kinematics in this setting, the scalar-type and pseudoscalar-type ALP conversion amplitudes interfere coherently, making both the photon-to-ALP conversion probability and the polarization rotation depend on the difference between the probe polarization angle $α$ and the coupling angle $θ_g$. Conversion is maximal at $|α-θ_g|=90^\circ$, where the polarization rotation vanishes, while the rotation magnitude peaks at $α-θ_g=45^\circ$ modulo $90^\circ$, where conversion is half-maximal. These complementary polarization-angle dependences provide polarization-resolved signatures of mixed scalar--pseudoscalar photon couplings.

We show that several potential-energy functions based on the exponential function $e^{-αr}$, $α> 0$, are either equivalent or identical to the Tietz potential. Some of those potentials exhibit redundant parameters that can be removed without affecting their performance for the description of the vibration-rotation spectra of diatomic molecules.

Neural network fractional quantum Hall (FQH) states offer a promising alternative for capturing Landau level (LL) mixing and for understanding FQH physics, yet the incorporation of physical priors has so far been limited to the minimal exact constraints built into the ansatz. Working in spherical geometry, we show that the network's flexibility suffers both when only minimal additional physical priors are supplied and when priors such as flux attachment are imposed rigidly. In the former case, the monopole harmonic product orbital (MHPO) ansatz is difficult to optimize, whereas in the latter, the expressivity of the neural network is restricted. We therefore propose the orbital pair matrix factor MHPO (MHPO-M) ansatz, which balances physical priors against flexibility by not only replacing the fixed Laughlin structure with learnable pair factors but also making them dependent on both the electron configurations and the orbitals. Across $ν=1/5$, $1/3$, and $2/5$, MHPO-M achieves the lowest variational energy among the tested variants, and a factorized orbital readout based on it enables scaling to 35 electrons, with energies competitive with trends inferred from three-LL exact-diagonalization results. These results demonstrate that physical priors can be appropriately incorporated without sacrificing the flexibility of neural network wavefunctions, opening a promising path toward accurate, scalable modeling of FQH systems with LL mixing.

In single-shot Bayesian multiparameter quantum estimation, measurement incompatibility can increase the minimum joint quadratic loss by at most a factor of two relative to the bound obtained by optimising each parameter separately. Using the generalised Barnum--Knill inequality, we establish the same bound for a wider class of additive losses generated by positive score functions, showing that this limitation extends beyond the standard quadratic setting. To illustrate this result, we consider a broad family of periodic losses, including the sine loss sometimes employed in interferometry, and derive the corresponding incompatibility bound for Bayesian multiphase estimation with arbitrary prior knowledge. We further extend the framework to unbounded losses, such as absolute losses; this also recovers the case of quadratic losses.

Electrons in graphene move like massless relativistic particles, making them exceptionally mobile but difficult to trap because Klein tunnelling permits unimpeded passage through electrostatic barriers. This challenge extends to atomic collapse and hadron confinement. Twisted trilayers form Bernal and rhombohedral domains joined by smooth boundaries, bringing their carriers into contact. Here we show that a new mechanism, distinct from established approaches, confines massless fermions in equilateral triangular Bernal domains without mass barriers, bulk gaps or physical edges. Simulations and analytical modeling reveal that massless carriers have no adiabatic continuation into rhombohedral domains, while escape through nonadiabatic coupling to massive carriers is exponentially suppressed by smooth stacking variation. Perfect reflection in the adiabatic limit turns Bernal domains into quantum cavities in a gapless, edgeless metal. Striking density-of-states oscillations encode Eisenstein-integer arithmetic, linking energies and degeneracies to norms and prime factorizations. These findings bring relativistic confinement and number theory into experimentally accessible electronic spectra.

We study how the one-dimensional deformation suggested by nonadditive $q$-calculus can be extended to a rotationally covariant quantum model and what observable consequences follow from this extension. We choose a radial extension about a distinguished center in which only the radial derivative is deformed, while tangential derivatives retain their ordinary form. Within this model, we construct self-adjoint frame-momentum operators and derive a rotationally invariant uncertainty bound with a correction proportional to the mean distance from the center. We then adopt a non-negative kinetic Hamiltonian built from these momenta and derive the leading harmonic-oscillator energy shifts for weak deformation. The energy corrections split the levels with different orbital angular momenta that are degenerate in the undeformed oscillator, while preserving the degeneracy associated with rotational symmetry.

We theoretically introduce a quantum-circuit synthesis protocol to realize any $n$-qubit transformation $U\in U(2^n)$, up to a diagonal. The resulting circuit is directly native to and optimal in gate count and depth for systems where bitstring-conditioned rotations with tunable angle and axis, $C^{(n-1)}R(θ,φ)$, form the set of native operations. Subsequently, we suggest how this protocol can be implemented in a few-mode superconducting circuit, and experimentally demonstrate the method for the smallest nontrivial case, i.e., for two qubits. We report an average gate fidelity of 97.6 % for Haar-random two-qubit unitaries up to phase shifts in the computational basis. Importantly, these results suggest that multimode devices, such as those in the multimon or multiunimon families may become competitive with qubit-array networks for general-unitary implementations for qubit counts as low as three.

The exact multi-resolvent hierarchy of dense many-body spectra encodes higher-order spectral-weight correlations, but closing it predictively for interacting Hamiltonians remains a challenge. We introduce the multi-resolvent self-consistency (MRSC) equations, which separate an exact algebraic hierarchy from an approximate finite-parameter closure. The exact Feshbach geometric identity organizes r-resolvent cumulants into a ladder over irreducible vertices Gamma^(r), and the projected hierarchy expresses those vertices as functionals of the cumulants. The closure works in finite parameters: a connectivity basis organizes a general Hamiltonian's seed into class amplitudes, and a causal r-fold Stieltjes representation with a moment-field identity reduce moment matching to a finite-dimensional problem closed at a predictive fixed point. On the free-fermion benchmark the tested exact identities are reproduced and the Faddeeva closure is recovered at r=1. In a blind test on the interacting Ising chain, with the exact two-resolvent data withheld, the Hamiltonian-derived closure predicts the tested probes to 0.35%-0.97%. At the observable level the exact two-resolvent sector supplies a sign-correct, energy-resolved correction to the single-resolvent baseline for the off-diagonal eigenstate-thermalization-hypothesis (ETH) variance, of order one relative to it. Closure errors organize hierarchically: a level-by-level deficit decomposition, anchor measurements of the isolatable terms, and an explicit propagation bound. The same moments further yield a diagnostic chain for the window conditions of local rotational invariance -- an exact drift-kernel identity, a proven single-state identifiability boundary, and a transferability census over couplings and realizations -- a finite-order framework, not a proof of universal emergence.

Thin-film spontaneous parametric down-conversion, due to the relaxed phase-matching condition, generates photon pairs that are extremely broadband in frequency and angle and highly entangled in time/frequency and position/momentum. Here we show that it also provides a very broad orbital angular momentum (OAM) spectrum, which, in contrast to the case of bulk crystals, is decoupled from the frequency spectrum. To demonstrate it experimentally, we generate photon pairs in a $7~μ\mathrm{m}$-thick lithium niobate film and compare them with those from a $500~μ\mathrm{m}$-thick periodically poled lithium niobate crystal under identical pump conditions. The thin-film source exhibits a substantially broader OAM spectrum, with the azimuthal Schmidt number almost 9 times larger than that of the bulk source. On this highly entangled state, we perform quantum-state tomography in selected two- and four-dimensional OAM subspaces, demonstrating high-purity maximally entangled states. These results highlight thin nonlinear films as a promising platform for high-dimensional quantum-state generation with weak spatial--spectral coupling.

The Unruh effect links acceleration to thermalization, providing a relativistic setting for anomalous quantum relaxation. We demonstrate a {\it relativistic} strong quantum Mpemba effect in the Unruh thermalization of a two-level detector coupled to a massless scalar field. For a fixed pair of isospectral initial states, relaxation curves that never cross in inertial motion exhibit a Mpemba crossing above a threshold acceleration. At a higher, precisely tuned acceleration, the initially farther state has zero overlap with the slowest decay mode and relaxes with a faster asymptotic exponential rate. We identify how competition between transition and dephasing channels governs the relaxation spectrum, where sufficiently strong longitudinal coupling enables acceleration to switch the relaxation bottleneck between population and coherence modes. We derive the spectral-switching condition and construct isospectral preparation protocols that eliminate slow-mode contributions within their physical domains. These protocols reveal how coherence can suppress or enhance slow-mode overlap at fixed purity, depending on the underlying spectral structure. Our results establish acceleration as a control parameter for anomalous quantum relaxation, connecting relativistic quantum dynamics with nonequilibrium thermodynamics.

Optimal approximate state conversion is a fundamental task in quantum resource theories, yet existing solutions are largely tailored to specific distinguishability measures and resource theories. We show that every optimal approximate-conversion problem in the three paradigmatic majorization-based quantum resource theories of non-uniformity, bipartite pure-state entanglement, and pure-state coherence reduces exactly to one of only four elementary taut-string constructions. This holds for problems generated by Schur-convex spectral distances and by a broad family of quantum divergences satisfying a natural reduction property with respect to the corresponding equivalence group. The resulting framework encompasses a broad class of physically relevant distinguishability measures, including the trace distance, all unitarily invariant norms, quantum relative entropy, maximal quantum $f$-divergences, and the $α$-$z$ Rényi relative entropies. The increment vector of the corresponding taut string completely determines both the optimal approximation error and a canonical optimal state. Our results establish a common geometric framework for approximate quantum resource conversion, revealing that a broad class of seemingly different optimization problems is governed by the same taut-string geometric principle.

The measured logical error rate of a quantum low-density parity-check (QLDPC) code depends on the decoding algorithm. We develop a framework that certifies non-degenerate maximum-likelihood (ML) decoding outcomes on individual sampled shots under circuit-level noise, providing a common reference for comparing decoders and codes. Upper and lower bounds on the minimum correction cost in the true and competing logical classes establish success, failure, or an undecided outcome. Branch-and-bound search refines these intervals while retaining valid bounds under resource limits. Counting the outcomes bounds the empirical ML logical error rate, with interval width equal to the undecided fraction. Results for two bivariate bicycle codes show that best-first ordered statistics decoding (BF-OSD) tracks the non-degenerate ML benchmark closely while leaving some ML-correctable shots.

Ions possess both center-of-mass motion and internal states, rendering trapped-ion optical clocks susceptible to perturbations of both degrees of freedom, which results in systematic shifts and fluctuations with motional and relativistic origins. We develop a quantum theory that connects these effects to filter functions determined by the employed pulse sequences and show how the interrogation can be tailored to suppress or enhance specific perturbations. Our treatment includes laser frequency noise and motional effects such as recoil and Doppler shifts, micromotion and excess micromotion, as well as state-dependent trap imperfections and accelerations, e.g., caused by Stark shifts. We further account for relativistic effects including time dilation and the mass defect, and show how the same framework can be applied to hypothetical dark-matter signals. By considering ensemble-averaged phases and their variances, we characterize both systematic shifts and fluctuations, while asynchronous operation relative to the Paul-trap drive allows motional fluctuations to average down between runs. Our results provide a unified framework for characterizing and controlling the systematic and statistical contributions that determine the trueness and precision of trapped-ion optical clocks.

The Fer expansion writes the propagator of a driven quantum system as an ordered product of exponentials, each generated by the time integral of an effective Hamiltonian that governs the evolution left over by the previous factors. It can be stopped after finitely many factors whenever this leftover evolution is known in closed form, for instance when the effective Hamiltonian commutes with itself at all times, or precesses about a fixed axis with constant angular velocity. For $\mathfrak{su}(2)$, in any representation, from a qubit to a spin of any size, we resum the Fer recursion into a closed map on curves in $\mathbb{R}^3$. We prove that, for a real-analytic drive, in both cases the expansion stops beyond the first factor only trivially, when the first exponential is already exact.

We show that, starting from the same state, optimal driving can sometimes reach a colder (or hotter) target in the same amount of time while dissipating less energy, or equivalently dissipate the same amount of energy in a shorter time. We study this counterintuitive phenomenon in the slow-driving regime of an open quantum system, where we name it Near-Equilibrium Anomalous Tradeoff (NEAT). We establish necessary conditions for its occurrence and show its underlying geometric origin. While NEAT is reminiscent of the well-known Mpemba effect, the two phenomena are distinct in general. We demonstrate NEAT in an exactly solvable qutrit model, as well as for d-dimensional birth-death dynamics with independently controlled energy levels. Finally, we show how NEAT can improve the performance of Carnot engines.

We establish sufficient conditions for two-way local quantum-channel stability in classical $\mathbb Z_2$ lattice gauge models with spins on $m$-dimensional cells of a $d$-dimensional lattice. Each interaction multiplies the spins on the boundary of an $(m+1)$-cell. This family, defined on the full spin Hilbert space without a Gauss-law constraint, includes the Ising model at $m=0$ and the magnetic sector of the toric code at $m=1$. The low-temperature proof combines two ingredients: locally indistinguishable flat sectors and extended magnetic defects of dimension $d-m-1$. For $1\le m\le d-2$, sufficiently weak local classical perturbations at sufficiently low positive temperature preserve equivalence to the canonical flat ensemble. No internal or gauge symmetry is required of the perturbation. For weak noncommuting perturbations, we prove the same conclusion in a smaller sufficient window by reducing the diagonal probabilities to a weak classical interaction and recovering the coherences with a local channel. The conversion channels use product ancillary inputs, have polylogarithmic causal radius, and achieve any prescribed inverse-power whole-system trace-norm error. Sufficiently high-temperature states are instead two-way equivalent to a product state. Independent finite-dimensional onsite systems can be included with weak local couplings. An optimized covariance between two distant neighborhoods of parallel $m$-tori is nonincreasing under one-way local conversion and invariant under two-way conversion. Its values $\mathcal F_m=1$ and $0$ distinguish the proved low- and high-temperature domains without a protecting symmetry. These sufficient domains do not determine the full phase diagram.

Quantum amplitude estimation offers a theoretical quadratic speedup over classical Monte Carlo methods for financial derivative pricing. However, extending gate-based algorithms to path-dependent barrier options has historically been hampered by sequential path discretization, where tracking price paths across $d$ monitoring dates incurs a linear escalation in qubit footprint and gate depth ($\mathcal{O}(d)$), posing severe coherence challenges for near-term quantum processors. In this work, we present a constant-depth quantum pricing framework that fundamentally eliminates the temporal dependency of barrier monitoring. Leveraging the Brownian reflection principle and Girsanov theorem, we project the continuous supremum dynamics onto a static bivariate joint distribution of the terminal price $S_T$ and running supremum $M_T$. This allows decoupling dynamic boundary checks into a static bivariate oracle comprising two parallel comparators and a dual-controlled rotation gate. We prove this architecture reduces circuit depth and comparator complexity from $\mathcal{O}(d)$ to an invariant $\mathcal{O}(1)$, while supporting discrete monitoring via zero-quantum-cost boundary corrections. Transpilation benchmarks for daily monitoring ($d = 252$) show our framework slashes physical CNOT count by 98.59% (from 2262 to 32) and compresses two-qubit depth by 98.02% (from 1514 to 30 layers). Under a realistic 127-qubit IBM Eagle noise model, the shallow circuit achieves a 7.84% relative valuation error with M3 readout mitigation. Finally, the framework seamlessly extends to nonlinear exotic payoffs lacking analytical solutions, establishing a noise-resilient pathway toward practical quantum advantage in computational finance.

Unstructured meshes are widely used in modelling and simulation in Computational Fluid Dynamics (CFD) due to their geometric flexibility. However, they require an efficient block encoding circuit describing the system. Here, we present a new block encoding methodology for unstructured mesh solvers based on decomposing the system matrix into a sum of 1-sparse matrices. This block encoding is engineered to reduce subnormalisation even in the absence of structure by hiding the contribution of large matrix elements behind others. We investigate three methods of 1-sparse decomposition. Our circuit constructions can optionally take advantage of limited matrix bandwidth and repeated values. For example we consider digitisation (reduced precision), where the number of multiplexed rotation gates is equal to the number of non-unique matrix entries. We evaluate our methodologies using 2D and 3D CFD matrices for unstructured aerofoil meshes, structured cavity, and duct meshes, with and without matrix preconditioning. Our results show that we are able to achieve a block encoding with a near constant subnormalisation factor as the number of matrix preconditioning infill levels increases. This significantly reduces the subnormalised condition number and, in one case, reduces the degree of the QSP polynomial approximation to $1/x$ by 100,000. Reduced precision digitisation is shown to become more effective as the number of preconditioning infill levels is increased and, in one case, reduces the number of multiplexed rotations from 2,785,576 to 546 whilst maintaining an infidelity of $2.6\times10^{-5}$ relative to the classical solution. The effect of digitisation on QSVT solutions is demonstrated using 2D and 3D unstructured mesh aerofoil cases. Due to its flexibility and automatic applicability, we believe our 1-sparse decomposition block encoding can offer benefits to other quantum applications.

Dipolar Bose--Einstein condensates (BECs), i.e., BECs with long-range dipole-dipole interactions (DDI), exhibit extraordinarily rich physics and serve as a versatile experimental platform for exploring exotic quantum states of matter. Within the mean-field framework, a dipolar BEC can be described by the Gross--Pitaevskii (GP) model with a DDI term. Its stationary states consist of the ground state, which minimizes the GP energy functional under the normalization constraint, and excited states, which are higher-energy critical points that typically correspond to constrained saddle points. Excited states encode collective excitation modes and play a key role in the dynamical stability and quantum phase transitions of cold-atom systems. However, in contrast to the extensively studied ground state, they remain far less explored numerically, especially in dipolar systems. In this work, we develop a numerical method based on the constrained gentlest ascent dynamics (CGAD) that systematically computes excited states of dipolar BECs by stably targeting constrained saddle points with any prescribed Morse index. Specifically, a semi-implicit sine-pseudospectral discretization with an orthonormalization correction step is adopted, and the nonlocal DDI terms are evaluated efficiently and accurately via the nonuniform fast Fourier transform (NUFFT). The resulting scheme is applied to one-, two-, and three-dimensional dipolar BECs, enabling a detailed numerical investigation of their excited states. Remarkably, our simulations reveal that excited states can persist even in regimes where the ground state of the condensate becomes mean-field unstable. This work provides a computational framework for studying excited states in dipolar quantum gases and offers insights for future theoretical and experimental investigations.

Using contour-integral representations of the permanent and of the Hafnian, we turn the computation of their moments for random matrices into a replica calculation, analogous to that of the moments of the partition function of a mean-field spin glass. For the $2k$-th moment of $N\times N$ matrices with independent entries, the dominant saddle point is replica symmetric for $k>2$, and we obtain in closed form the exponential growth rate, the prefactor and the first $1/N$ correction, in agreement with exact enumerations. The growth rate depends only on whether the entries are real or complex; higher cumulants affect only the prefactor and the $1/N$ term. At $k=2$ the replica-symmetric solution becomes unstable, separating a power-law bulk of the distribution from a large-deviation tail, which we compute. The results apply to boson sampling with single photons and with squeezed light.

Atmospheric turbulence and channel loss represent the primary limiting factors in ground-to-satellite quantum communication systems, yet their joint impact remains insufficiently characterized across diverse operational conditions. In this work, we develop a comprehensive and open atmospheric channel model for quantum optical links along ground-to-satellite paths, integrating altitude-dependent molecular and aerosol absorptions. The model is validated with available data from missions such as Micius and Hispasat, including a secondary viability assessment for a hypothetical Starlink-based quantum communication network, where we evaluate the predicted channel behavior in terms of single-photon transmittance and power balance, alongside the channel capacity of the link for uplink and downlink exclusively. Our comparative analysis demonstrates the ability of our channel model to predict real data under simple atmospheric behavior assumptions, which offer practical guidelines for the design and optimization of future quantum satellite missions.

Concatenation of quantum repeater nodes has been proposed as a means to distribute entanglement efficiently across future long-distance networks. Here, we demonstrate a trapped-ion repeater node that establishes photonic entanglement over a 17 km fiber traversing a city, moving beyond laboratory-only prototypes. The node comprises two atomic ions coupled to an optical cavity. First, a detailed characterization is performed of the long fiber channel and of ion-photon entanglement distributed across it. Next, a repeater-node protocol is implemented, achieving entanglement between a local photon and a remote photon with a Bell-state fidelity of $81.6^{+1.9}_{-1.4}\%$. These results demonstrate that trapped-ion repeater-node technology can operate over existing city-scale fiber infrastructure and represent a step toward distributed quantum repeater networks.

High-fidelity entangling gates are essential for quantum information processing. In transmon circuits, higher excited states provide additional pathways for engineering interactions within the computational subspace. Here we demonstrate controlled-Z (CZ) gates that exploit two noncomputational states, $\ket{02}$ and $\ket{20}$, through selective Floquet coupling. The nontrivial parametric modulation can activate both auxiliary transitions from $\ket{11}$ while suppressing the leading exchange between $\ket{01}$ and $\ket{10}$. Based on this approach, we develop two gate protocols: a nonadiabatic round trip through a bright auxiliary superposition and adiabatic evolution along a zero-energy dark state, both achieving average gate fidelities above $99.99\%$ in numerical simulations. Control of the modulation phase further extends the bright-state protocol to conventional and unconventional geometric CZ gates. Effective-model simulations show that unconventional control improves tolerance to residual $ZZ$ coupling and static qubit-frequency offsets relative to conventional control over the parameter ranges examined. Simulations including neighboring spectator qubits show that the original nonadiabatic bright-state and adiabatic dark-state CZ protocols retain high gate fidelities. This framework offers new routes toward the experimental realization of CZ gates and their geometric implementations.

Understanding the three-dimensional (3D) quantum Hall effect, characterized by a Chern vector rather than a single Chern number, has been a central pursuit in topological physics. While quantized Hall transport is established for the special case with one nonzero Chern component, recent realizations of more general Chern-vector states raise a fundamental question: how does such topology protect quantized transport? Here, we predict a distinct 3D quantized Hall effect protected by $\mathbf{C}=(0,m,n)$. For samples with dimensions $L_y$ and $L_z$, global topology enforces collective quantization of $mL_y+nL_z$, despite the fragility of individual edge modes to disorder. This reveals a novel transport regime in which robust quantization emerges as a holistic property of a unified chiral network,rather than of its constituent modes. Crucially, this collective response manifests as a quantized Hall conductance $G_{xy}=\pm(mL_y+nL_z)e^2/h$, with a distinctive dependence on both Chern-vector components and sample dimensions. We propose candidate materials to facilitate experimental observation.

We theoretically investigate narrowband nonreciprocal transmission in a Doppler-broadened five-level M-type atomic medium. After Doppler averaging, the M-type system retains a narrow near-resonant electromagnetically induced transparency window that is narrower than that of a standard three-level $Λ$ system. This spectral narrowing is associated with the decreasing separation between the two inner dressed states as atomic velocity increases. The transparency window exhibits pronounced direction-dependent transmission, with high forward transmission and strong suppression in the reverse direction. The transparency linewidth and forward-backward probe transmission can be controlled via two independent driving fields, while the central transparency frequency is kept essentially unchanged. The resulting narrowband nonreciprocity supports high forward transmission together with strong suppression in the reverse direction, which is suitable for frequency-selective optical filtering and nonreciprocal optical transmission in thermal atomic media. Our scheme with these specific features is geared towards enabling compact vapor-cell-based nonreciprocal devices for quantum network applications.

Symmetry-protected ground-state crossings can produce exact first-order transitions (FOTs) even at finite $N$, in contrast to continuous transitions governed by soft-mode criticality. We establish exact Juddian ground-state crossings for arbitrary finite $N$ in the one- and two-photon anisotropic Dicke models and identify a common two-channel structure: the eigenvalues of the coupling matrix set the local normal-state instability thresholds, whereas its determinant fixes the exact crossing. Despite this common structure, the resulting FOTs have distinct fates determined by the bosonic response. In the one-photon model, the overlap between coherent Juddian branches vanishes in the thermodynamic or infinite frequency-ratio limits, asymptotically suppressing the FOT cusp. In the two-photon model, squeezed Juddian states lose normalizability at spectral collapse, thereby terminating the physical FOT line at finite $N$. Although the cusp strength tends to zero as the endpoint is approached, the terminating FOT retains a collective spectral signature: the different-parity gap is predicted to close with an $N$-dependent exponent $μ_N=(2N+3)/4$, one greater than the cusp termination exponent. By contrast, the same-parity soft mode retains $N$-independent square-root scaling and governs the critical response. Thus spectral collapse can terminate an exact finite-$N$ FOT while preserving its collective imprint in the parity-resolved spectrum.

We propose an approximate classical algorithm for estimating quantum circuits' transition amplitudes, $\langle Ψ_f | \hat{U} | Ψ_0 \rangle$, based on Monte Carlo sums over bidirectionally sampled Feynman paths. The algorithm generates Feynman paths, i.e., sequences of intermediate computational basis states, by combining information from random walks initiated at both the input and output states, $Ψ_0$ and $Ψ_f$, respectively. It further combines this bidirectional approach with Multiple Importance Sampling, a powerful variance reduction technique that avoids variance peaks caused by divisions by the very low sampling probabilities associated with hard to reach paths. Empirical data demonstrate the superior convergence rate exhibited by the bidirectional algorithm over a unidirectional, forward-only sampling approach. This superiority is due to the effectiveness of the proposed algorithm in finding and weighting paths with non-zero amplitude in an extremely sparse path space. Sum of paths algorithms exhibit very favourable space complexity. Monte Carlo replaces exhaustive enumeration of the exponentially large path space by stochastic sampling, the computational cost being determined by the variance of the estimator. This work demonstrates these two features by presenting results on very large quantum circuits, with up to 4096 qubits.

Axions are a compelling dark matter candidate suggested by theories beyond the Standard Model. The predicted axion-electron coupling and the resulting pseudomagnetic field allow for laboratory axion searches. Here we report an experimental axion search via a superconductor-spin hybrid magnetometer. A state-of-the-art broadband magnetometer with a sensitivity of sub-100 aT/Hz$^{1/2}$ at tens of kHz has been realized by coupling a ferrite spin sensor to a readout system based on a superconducting quantum interference device. The most stringent terrestrial constraints on the axion-electron coupling have been established in the frequency range 5$\sim$60 kHz. In the future, an improvement on the constraints of more than 4 orders of magnitude is foreseeable through arrays of superconductor-spin hybrid magnetometers with optimized designs. This work demonstrates the potential of superconductor-spin hybrid magnetometers in high-precision magnetic field sensing and the study of fundamental physics.

We demonstrate K-band nondegenerate three-wave-mixing amplification in a multimode resonator comprising an array of 500 SNAILs. Pairing K-band signal modes with lower-frequency internal idler modes enables 20 dB of gain continuously from 19.6 to 25.6 GHz with pump frequencies below 32.2 GHz. At 20 dB gain, the 3-dB bandwidth ranges from 2.6 to 11.7 MHz, and the input-referred 1-dB compression power reaches -100.9 dBm. In the 20-22 GHz band, the average added noise is 0.73 quanta. A two-mode nondegenerate parametric amplification model describes the measured gain response and gain-bandwidth behavior, while a multimode Kerr model captures the overall compression scale. Our amplifier provides a practical solution for implementing a state-of-the-art readout of superconducting qubits in the K-band.

The detection of axion dark matter poses a significant challenge due to its exceptionally weak coupling to standard-model particles. Here we develop a noise-tolerant quantum-metrology scheme based on coupled $^{129}$Xe spin ensembles to search for such weakly interacting particles. Within an experimentally accessible parameter regime, our scheme achieves an ideal exclusion limit on the axion coupling constant that is several orders of magnitude more stringent than that of conventional detection methods. We further investigate the performance of our scheme under dissipative noise and find that its robustness is fundamentally governed by the energy-spectrum structure of the composite spin-environment system. Remarkably, when a bound state emerges in the spectrum, the exclusion limit asymptotically recovers its ideal value in the non-Markovian dynamics, whereas under the Markovian approximation the limit deteriorates significantly due to noise. Our results establish a universal mechanism for noise-resilient exploration of beyond-standard-model physics, which can be practically implemented by engineering bound-state formation via tuning the Larmor frequency of the spin ensembles.

Treating the arrow of time as a controllable quantum variable rather than a fixed external parameter is a central challenge in quantum physics. Recently, Bloch~\cite{Bloch2025} proposed the theoretical concept of a \emph{time qubit}, a two-level control space $\mathcal{H}_T=\mathrm{span}\{\ket{+},\ket{-}\}$ that selects between opposite Hamiltonian evolutions $\hat{H}_{\pm}=\hat{H}_0\pm\hat{V}$, but this paradigm has remained experimentally unrealized. Here we formulate the quantum-optical theory of a single-photon time qubit---uncovering quantum-vacuum control and complementarity of the arrow of time---and experimentally probe and validate its predictions using phase-resolved single-photon interferometry from two coherently seeded entangled nonlinear biphoton sources~\cite{Lee2018,Yoon2021}. First, we show theoretically and verify experimentally that a controlled $π$ pump--seed phase inversion during pair creation from the quantum vacuum flips the stimulated displacement generator $\hat{V}\to -\hat{V}$ on top of the spontaneous two-mode squeezing background $\hat{H}_0$, reversing the stimulated evolution time [$\hat{U}_{\mathrm{stim},-}(t)=\hat{U}_{\mathrm{stim},+}(-t)$] and enabling universal single-qubit $\mathrm{SU}(2)$ control and postselection-free first-order tomography on the temporal Bloch sphere. Second, we prove that spontaneous idler vacuum fluctuations record complete which-branch (temporal-direction) information whereas the shared coherent seed erases it without cascading or aligning the idler beams, establishing an exact wave--particle complementarity law $|\bm{r}|=\mathcal{V}=|α|^2/(1+|α|^2)$ for the purity of the arrow of time and enabling direct first-order measurement of the Loschmidt time-reversal echo.

How macroscopic definite outcomes and nonlocal correlations emerge from entangled superpositions across spacelike-separated regions without superluminal action or {\it ad hoc} wavefunction collapse remains a defining open question in the foundations of quantum mechanics. Here, we resolve this century-long paradox within \textit{linear} relativistic quantum electrodynamics by developing an open-system and measurement-defined framework realized in dual, spacelike-separated nonlinear crystals driven synchronously by a multi-mode optical frequency comb and seeded by an ultra-narrow coherent laser. Expanding the transverse electromagnetic vector potential into discrete single-photon frequency-comb supermodes, we show that tracing out the unmeasured continuous-wave idler field yields an exact spatial dephasing Lindblad master equation whose decoherence rate is governed by the non-orthogonal state overlap of single-photon-added coherent states. Connecting this open-system map to free-vector-space quotient measurement theory, we demonstrate that single-particle interference arises from the geometric projection of the composite state onto detector-defined conditional cosets rather than remote collapse, establishing strict operational equivalence across pump, seed, and signal phase scans. The resulting wave-particle-entanglement triality equality $P^2 + E^2 + V^2 = 1$ is saturated across the complete parameter space, while the atomic-clock-referenced comb structure anchors continuous-variable time-frequency displacement stabilizers directly at the hardware layer. Our work unifies induced coherence, Bohr's complementarity, and quotient measurement theory, providing a microscopic pathway toward fault-tolerant bosonic quantum information processing.

Stabilizer Rényi moments depend on a choice of operator basis and need not be determined by entanglement spectra. In this paper, we study their spatial decay in critical quantum chains described by two-dimensional conformal field theories. We derive an exact entanglement baseline for reductions of pure stabilizer states and a symmetry selection rule for the charged contribution at fixed support. An exact Ising example shows that an on-site rotation changes the full decay exponent while preserving every subsystem entanglement spectrum. For growing Ising intervals at index two, we obtain an exact Pfaffian representation and compare the charged amplitude with a candidate conformal boundary calculation. The data support this prediction, but its identification with the lattice limit still requires endpoint matching and control of the order of limits.

It has been shown that Discrete Time Crystal (DTC) behavior may arise in the periodically driven, open Dicke model in the thermodynamic limit ($N \rightarrow \infty$). In this work, we demonstrate that finite $N$ non-mean-field fluctuations in this model can lead to decay rates and amplitudes of transient DTCs that display a non-trivial non-monotonic behavior with an increasing number of atoms. We show that the second-order cumulant expansion fails to capture the finite-size dynamics, while a stochastic version of the Truncated Wigner Approximation (TWA) is remarkably accurate, particularly in the large atom ensemble limit. Using the TWA and the Monte Carlo Wave Function (MCWF) approach, we identify three distinct dynamical regimes of transient DTC behavior in the finite-size Dicke model. We outline the mechanism behind the non-monotonic finite size dynamical decay of DTC order and discuss the implications for experiments performed on finite-sized atomic assemblies.

Universal information extracted from entanglement at a critical point is commonly associated with the long-distance properties of the bulk state, while microscopic details of a lattice bipartition are expected to be washed out under coarse graining. Counterintuitively, we show directly that such microscopic information can survive in the statistical ensemble that determines the second Rényi entropy and obviously change the physics there. Using quantum Monte Carlo simulations of the square-lattice $J$-$Q_3$ model at the Néel--valence-bond-solid (VBS) transition, we measure magnetic and dimer order parameters in the Rényi-2 ensemble. For a standard axis-aligned bipartition, the VBS component perpendicular to the entanglement boundary remains finite in the thermodynamic extrapolation and is inequivalent to the parallel component, while the Néel order vanishes. For a $45^\circ$ tilted bipartition, in contrast, the two VBS components remain equivalent within numerical accuracy. We interpret this contrast in terms of the Rényi twist defect: the two bipartitions have the same bulk theory but realize different microscopic defect symmetries. Our results demonstrate that lattice information invisible to the bulk continuum theory alone can remain active in the long-distance Rényi ensemble, providing a microscopic explanation for the strong bipartition dependence previously observed in entanglement studies of deconfined criticality.

We develop smooth hybrid lattice surgery for group surface codes, enabling joint logical measurements through merge and split operations along smooth boundaries. The code patches may correspond to identical or different finite groups, including non-Abelian groups. Our central result is that smooth merge and split realize a logical $K$-coset measurement, where $K$ is the subgroup defining the interface. This generalizes the joint logical parity measurement of ordinary surface codes. Using a tensor-network representation, we derive explicit measurement circuits and develop procedures for correcting nonidentity measurement outcomes. We illustrate the framework through a generalized controlled multiplication gate between group surface codes and protocols for preparing the $T$, $CZ$, $CCX$, and $CS$ magic states, producing resources encoded in one or more $\mathbb{Z}_2$ surface code patches. Our results show how smooth hybrid lattice surgery broadens the range of logical operations available for group surface codes.

Coexistence of classical and quantum light in optical fiber is a key requirement for scalable quantum networks. However, it is fundamentally limited by nonlinear crosstalk from intense classical signals. Hollow-core fiber (HCF), with its intrinsically low optical nonlinearity, offers a promising solution. Here, we experimentally demonstrate the coexistence of polarization-entangled photons with dense wavelength-division multiplexed (DWDM) classical signals with a total launch power of 11.2 dBm, and perform a direct comparison between equal-length single-mode fiber (SMF) and photonic-bandgap-based HCF deployed in a campus network. We observe that HCF suppresses background noise by approximately two orders of magnitude compared to SMF, while preserving high-fidelity entanglement distribution. Our results provide clear experimental evidence of the advantage of HCF and establish its potential as a transmission medium.

We investigate the electronic states of the K$_4$ lattice in a uniform magnetic field within a nearest-neighbor tight-binding model. The K$_4$ lattice is a \rev{noncentrosymmetric three-dimensional network with triple-Dirac cones at the $Γ$ and H points}. By fixing the Bloch momentum component parallel to the field, the Peierls-substituted tight-binding problem reduces to an effective two-dimensional problem and yields a Hofstadter spectrum \rev{whose self-similar subpatterns reflect the geometry of the lattice projected onto the plane perpendicular to the field}. A square-like substructure emerges on the flux scale $φ= 1/8$ for $\bm{B}\parallel[100]$, and honeycomb- and triangular-like substructures emerge on the finer scale $φ= 1/32$ for $\bm{B}\parallel[111]$\rev{. Here $φ$ is the flux through the elementary plaquette of the projected lattice, and these scales correspond to one flux quantum per projected unit cell. Owing to the screw axes of the chiral K$_4$ network, the field-parallel momentum acts as an additional flux, which, for commensurate values of this momentum, shifts the spectrum along the flux axis and brings the second triple-Dirac cone at the H point into the magnetic spectrum}. In the weak-field limit, we derive the Landau-level structure from a low-energy effective Hamiltonian around the $Γ$ point. The three-component nature of the triple-Dirac cone gives rise to a cubic secular equation, whose solutions describe how a pseudospin-flat branch coexists with two relativistic Landau ladders \rev{and a single chiral $n=0$ level dispersing linearly along the field, in agreement with the lattice calculation}.

We consider the DMPK ensemble, which models quantum transport in a disordered wire, and describe its limiting local statistics as the number of particles tends to infinity. In the metallic regime, as well as at crossover I, we obtain sine statistics in the bulk, Bessel statistics at the hard edge and Airy statistics at the soft edge. In the insulating regime, we prove localization around certain explicit deterministic positions with Gaussian fluctuations. This confirms and quantifies the predicted universal and localized behavior in the physics literature. At crossover II, we obtain explicit limiting kernels in the bulk and at both edges, which interpolate between these regimes. The hard edge kernel involves Legendre functions and, to the best of our knowledge, is new, while the bulk and soft edge kernels agree with those derived for the squared singular values of critically scaled products of independent Ginibre matrices. To explain these similarities, we construct a class of invariant pseudo-unitary matrices that is closed under taking products and use it to interpret the DMPK ensemble as the joint density of the spectral variables of a product of such random matrices. More generally, the latter takes the form of a polynomial ensemble of derivative type involving a second order differential operator compatible with the Legendre functions. Finally, we obtain uniform asymptotic expansions of the mean and variance of the conductance and prove that the DMPK ensemble admits universal conductance fluctuations, i.e. the variance of the conductance tends to $1/15$ throughout the whole metallic regime. This again confirms the predictions in the physics literature.

Photon loss is the dominant noise source in linear optical quantum circuits. Each lost photon turns an ideal n-photon outcome into a pattern with fewer photons, so the detector counts no longer follow the ideal output distribution, and the lossless events that do follow it become exponentially rare as the photon number grows. Discarding the lossy events (postselection) therefore wastes most of the data at realistic loss rates, and the ideal distribution has to be inferred from the lossy counts themselves. Recycling-based mitigation (Mills & Mezher, Quantum 2026; Quandela's photon_recycling) reweights lossy samples to recover lossless probabilities, but its estimators are biased and restricted to the no-collision sector, where each output mode holds at most one photon. We instead treat the raw counts as Multinomial observations under per-photon binomial loss and infer the ideal output distribution and the loss rate jointly from a Bayesian posterior, which extends naturally to outputs with collisions. On data from the independent Perceval simulator at the scale of prior work (n=4 photons in m=20 and m=10 modes), the posterior has lower KL divergence than both recycling and postselection at every tested loss rate in the no-collision benchmark. In the collision regime it recovers the loss rate and the collision-pattern probabilities, which recycling cannot estimate, and stays below recycling at every loss rate and below postselection except at low loss, where the two are comparable. Its advantage over recycling grows with the sample count, and it supplies credible intervals that the baselines lack.

With the rapid advancement of quantum computing, the security of traditional cryptographic systems is facing significant challenges. As a fundamental component of symmetric cryptography, block ciphers have attracted increasing attention regarding their quantum security in recent years. In this paper, we propose new quantum attacks on two Feistel-type constructions, i.e., New Structure IV and the lightweight block cipher LBlock, under the quantum chosen-plaintext attack (qCPA) model. First, we construct an 8-round quantum distinguisher for New Structure IV and perform an $r(r>12)$-round quantum key-recovery attack. Compared with Li et al.'s qCPA-based result presented at INSCRYPT 2024, our attack reduces the time complexity by a factor of $2^{n/2}$, where $n$ denotes the subkey length. Second, we design a 9-round quantum distinguisher for LBlock and extend it to an $r(r>15)$-round quantum key-recovery attack. The proposed quantum distinguisher covers one more round than Liu et al.'s automated-search distinguisher at ASIACRYPT 2025, which results in a $2^{16}$ reduction in the time complexity of our $r$-round quantum key-recovery attack on LBlock. Furthermore, by analyzing the structure of the round function and the key scheduling of LBlock, we reduce the subkey guess space for the 15-round attack from 76 bits to 52 bits, lowering the time complexity from \(O(2^{38})\) to \(O(2^{26})\) by a factor of \(2^{12}\).

Waveguides provide a flexible platform for long-range interactions between superconducting qubits. Here, we study how to engineer the effective \(XY\) and \(ZZ\) interactions between two qubits via qubit frequency assignments and multimode interference determined by the mode configuration and standing-wave parities of a finite multimode waveguide. For a single-mode waveguide, we find that \(XY\) and \(ZZ\) interactions cannot be simultaneously suppressed to zero and the residual qubit-qubit coupling always exists. For example, the \(XY\) interaction may be suppressed to a negligible level when two qubits and the waveguide mode satisfy the two-photon resonant condition, but the \(ZZ\) interaction cannot be switched off. For multimode configurations within the central dispersive window, the engineered interaction types are very different for odd and even numbers of modes. Even-mode configurations can readily produce strong \(XY\) interactions, whereas odd-mode configurations can strongly suppress the \(XY\) interaction while retaining a finite \(ZZ\) interaction. Full-Hamiltonian simulations of minimal two- and three-mode configurations confirm \(XY\)-dominated SWAP dynamics and \(ZZ\)-dominated CZ-type dynamics, respectively. These results establish a frequency assignment criterion of qubits and waveguide modes for selectively engineering long-range qubit-qubit interaction types induced by the waveguide with finite multimode.

Long-range interactions can protect dissipative order against fluctuations, but determining when they do so in two dimensions remains out of reach for existing many-body methods. We develop a continuous SU(2)-covariant truncated-Wigner framework that maps the problem onto stochastic dynamics with one Bloch sphere per site. Derived systematically from the exact Stratonovich-Weyl evolution of the Lindblad equation, it generates both drift and reservoir noise for arbitrary spin $S$. Benchmarks against exact and tensor-network calculations validate its description of non-equilibrium dynamics and steady states. Applied to 400-site two-dimensional dissipative anisotropic XY lattices, our method reveals physics missed by mean-field and perturbative approaches: vortex-antivortex proliferation destroys the predicted staggered-XY phase for nearest-neighbour coupling, whereas algebraically decaying interactions stabilize an extended $\mathbb{Z}_2$-ordered phase. We obtain the first beyond-mean-field steady-state phase diagram of the long-range interacting model, revealing reentrant loss of order at strong coupling and closure of the ordered region beyond $α\approx 3.5$. Our new method provides a scalable route to strongly correlated driven-dissipative systems with long-range interactions, higher-dimensional geometries, spin-boson couplings, and spins beyond one half, relevant to modern experiments with magnetic atoms and polar molecules in optical lattices and tweezer arrays.

We investigate the topological phase in a one-dimensional Su-Schrieffer-Heeger (SSH) chain in the presence of a finite concentration of non-Hermitian substitutional impurities. Our primary focus is the discovery of a deterministic mechanism to actively reconfigure the topological phase boundaries by introducing site-dependent, non-reciprocal intracell and intercell hopping amplitudes. Specifically, breaking the internal structural symmetry of the non-reciprocal impurity hoppings induces a targeted macroscopic displacement of the critical point. This mechanism allows for the controlled expansion or compression of the topological phase strictly via local defect asymmetry. We validate this boundary displacement through finite-size scaling analysis. The extracted correlation length critical exponents ($ν\approx 1.455$ and $ν\approx 1.397$ for symmetric and asymmetric configurations, respectively) confirm a disorder-induced departure from the pristine SSH universality class, with the exponent diverging at high defect densities. We also report an impurity-induced real-to-complex spectral transition geometrically characterized by the Non-Hermitian Skin Effect. Ultimately, our results establish how isolated non-Hermitian asymmetries cooperatively interact to deterministically shift macroscopic topological protection.

In this work, we demonstrate a dual-function, common-aperture free-space optical system that simultaneously supports decoy-state BB84 quantum key distribution (QKD) at 803 nm and bidirectional classical laser communication at 640/660 nm over a 10.31 km terrestrial link from a mobile platform to a stationary ground station. To the best of our knowledge, this is the first field demonstration of a fully integrated common-aperture architecture where a co-propagating classical optical link simultaneously performs full QKD post-processing and ecrypted payload transmission over a 10 km atmospheric channel. The classical link utilizes Manchester-coded on-off keying (MC-OOK) at 10 MHz, achieving a packet error rate of $\sim$ 0.4 $\%$ (estimated bit error rate (BER) of 3.13 $\times$ 10$^{-5}$) with hardware-based self-synchronization and error-packet retransmission. Over the 10.31 km link, the QKD system achieved an average quantum bit error rate (QBER) of 2.512 $\%$ and an average secret key rate of 644 bps using rate-adaptive low-density parity-check (LDPC) codes. Finally, using the distilled keys, real-time AES-256 encrypted image transmission was executed over the co-aligned classical optical channel, proving the feasibility of a completely self-contained, jam resistant mobile quantum optical network.

Addressing nonlinear numerical problems in quantum computing remains challenging, but several approaches, including Carleman linearization (CL), have been proposed to construct quantum algorithms for such problems. In this work, we develop a CL-based method for a high-dimensional nonlinear stochastic differential equation (SDE) $\mathrm{d} \mathbf{X}_t = \left(A(t) \mathbf{X}_t + F(t) \mathbf{X}_t^{\otimes s}\right) \mathrm{d} t + B(t) \mathrm{d} \mathbf{W}_t$ for an $\mathbb{R}^N$-valued random process $\mathbf{X}_t$, aiming at quantum speed-up with respect to the dimension $N$. We introduce auxiliary processes $\mathbf{Y}^j_t$ that approximate $\mathbf{X}_t^{\otimes j}$, derive a linearized system of SDEs for them, and obtain the linear ordinary differential equation (ODE) governing their expectations. We then apply a quantum ODE solver to it and, from the resulting quantum state, extract an estimate for the expectation of a linear function of $\mathbf{X}_t$ by overlap estimation. We show that, provided the nonlinear and noise terms in the SDE are sufficiently small relative to the linear term, the CL error decreases exponentially with the truncation order $J$ in CL, and we can estimate the target expectation with a ${\rm polylog}(N)$ number of queries to unitaries encoding coefficient matrices $A$, $F$, and $B$. Finally, we also run a numerical demonstration for an SDE related to Langevin dynamics, observing the exponential decay of the CL error as $J$ increases.

NVIDIA and Jülich Supercomputing Centre simulated a 104-qubit fault-tolerant quantum computing experiment on the JUPITER supercomputer, Europe's first exascale system. This simulation, detailed in an NVIDIA technical report, validated a magic state cultivation protocol that significantly reduces physical qubit overhead. The project utilized JUPITER's 8,192 NVIDIA GH200 Grace Hopper Superchips and advanced software to model complex quantum error correction. The post NVIDIA and Jülich Run 104-Qubit Magic State Cultivation Simulation on JUPITER Supercomputer appeared first on Quantum Computing Report .

The Korea Research Institute of Standards and Science (KRISS) has remeasured a key transition frequency of the strontium (Sr) atom for the first time in 88 years, since 1938, using a photonic grating chip. It has established a new absolute frequency value with a measurement uncertainty reduced by more than 50 times. By providing an accurate reference value for next-generation quantum technologies, this achievement is expected to contribute to the precise control and miniaturization of quantum devices, including atomic clocks and neutral-atom quantum computers. The work is published in the journal Metrologia.

Insider Brief Quantinuum reported 99.9995% logical fidelity on its Helios quantum computer using a color code, equivalent to five errors per million operations and a tenfold reduction from its previous result. Logical errors decreased exponentially as code distance increased, with each tested increase reducing remaining errors by a factor of 12. Tests on the same Helios hardware showed a tradeoff between codes, with Helix using 10 physical qubits per logical qubit while the color code used up to 37 but achieved lower logical error rates. Image: Rendering of a deployed Helios system. (Quantinuum) PRESS RELEASE &#8212; Quantinuum (NASDAQ: QNT), a leading full-stack quantum computing company, today announced a world-record quantum error-correction result, achieving a logical fidelity of 99.9995% on its Helios commercial computer using the company’s error-correction architecture. This marks Quantinuum ’s second breakthrough in two months, demonstrating how its highly accurate trapped-ion hardware and flexible architecture work together to deliver rapid improvements in accuracy. The achievement reinforces Quantinuum ’s error-correction leadership and validates that its accuracy performance is now within the target range for Apollo, the company’s planned universal fault-tolerant quantum computer expected to be available by 2029. Quantinuum ’s architecture is an end-to-end framework programmable through the company’s developer platform. It integrates tailored AI decoders, all-to-all qubit connectivity, high-fidelity physical operations, and hardware-level error correction. This architecture also allows the company to test, refine, and combine different error-correction codes and optimize between accuracy and efficiency. In the latest study, Quantinuum used a well-known “color code” within this architecture to achieve the world-record logical fidelity result, which is equivalent to just five errors per million operations. The error rate is 10 times lower than Quantinuum’s o

Voltage fluctuations, light fluctuations, temperature fluctuations—any fluctuations are troublesome and thus undesirable. They don't just cause discomfort; in engineering and medical applications, they affect the accuracy of measurements or introduce errors in controls. Even at the minute level of quantum phenomena, fluctuations are considered undesirable.

Quantinuum has demonstrated a 99.9995% logical memory fidelity on its Helios trapped-ion quantum computer, achieving a logical error rate of 5 × 10-6 per syndrome-extraction round on a distance-7 code. This performance shows exponential error suppression with increasing code distance, with a suppression factor of 12. These results align with the performance targets for Quantinuum's future universal fault-tolerant quantum system, Apollo. The post Quantinuum Demonstrates 99.9995% Logical Memory Fidelity on Helios Trapped-Ion Processor appeared first on Quantum Computing Report .

Insider Brief Chinese startup Tuoyuan, led by quantum researcher Mu Qiao, is pursuing neutral-atom quantum computing with a reported development target of 100 logical qubits. QbitAI reported that the company raised hundreds of millions of yuan in seed and angel financing, but those details have not been independently verified. Qiao has published research on neutral-atom and trapped-ion quantum simulation, while Tuoyuan has yet to disclose hardware benchmarks or a timeline for its planned system. Photo by Christian Lue on Unsplash A new Chinese startup led by quantum researcher Mu Qiao is pursuing neutral-atom quantum computing, with a reported development goal of building a system with 100 logical qubits. The company, identified as FlipFlop Tuoyuan in a QbitAI report republished by 36Kr , brings together Qiao’s experience in trapped-ion and neutral-atom experiments. Its reported plans focus on fault-tolerant computing, which uses error correction to protect calculations from the errors that limit quantum processors. QbitAI reported that Tuoyuan completed seed and angel financing totaling hundreds of millions of yuan &#8212; or tens of millions in U.S. dollars, citing people familiar with the company. The report named Source Code Capital, Oasis Capital and CICC Capital among the investors but did not provide an exact amount or valuation. Those financing details could not be independently verified for this article. Qiao’s research record provides better details on the technical experience behind the venture. He is a shared first author and a corresponding author of a study published in Nature in August 2025 that used an array of Rydberg atoms to investigate a quantum magnet with mobile vacancies, known as holes. Such experiments let researchers reproduce selected features of complex quantum systems under controlled conditions. The study examined interactions between magnetism and particle motion, a problem relevant to understanding strongly correlated materials, inclu

Today's computer technology, based on silicon chips, is slowly reaching its physical limits. Components cannot be miniaturized indefinitely, and clock speeds cannot be increased indefinitely. At the same time, huge AI data centers are being built in many places, and these consume an immense amount of electricity. This is why scientists around the world are searching for novel materials that can replace or complement silicon technology and consume significantly less electricity.

Insider Brief RIKEN researchers demonstrated high-accuracy parallel control of silicon spin qubits using a shared microwave line and a calibration method that reduces control errors. Pairwise phase calibrations helped maintain gate fidelities above 99.99% when operating up to three qubits simultaneously and approximately 99.9% across all five. Increased microwave power caused remaining losses in quantum coherence, identifying a limitation that further device improvements could help address. Image: Rendered illustration of five silicon spin qubits controlled in parallel through a shared microwave line. ( RIKEN ) PRESS RELEASE &#8212; Silicon spin qubits are a promising platform for building scalable quantum computers as they are compatible with the semiconductor manufacturing technologies used to produce today&#8217;s computer chips. However, they have an important weakness: silicon spin qubits typically lose accuracy when several qubits are under parallel control. To be useful, quantum computers will need to operate many qubits simultaneously without compromising the accuracy of their operations. Now, in a study published in Nature Physics , researchers from the RIKEN Center for Emergent Matter Science and collaborators have addressed this challenge by achieving high-fidelity control of multiple silicon spin qubits operating in parallel. Using a five-qubit silicon array controlled through a single shared microwave line, they identified a key source of errors during the simultaneous operation of qubits and developed a way to mitigate its effects. According to Leon Camenzind, a research scientist at RIKEN and co-first author who supervised the experiments, “This shows that high-fidelity control can be maintained even when several qubits are operated at the same time and represents an important step toward scaling up silicon-based quantum processors.” Unmasking the culprit behind control errors Quantum computers process information using quantum bits, or qubits, which

Xanadu, a photonic quantum computing company, has secured up to $10 million in additional DARPA funding through the Quantum Benchmarking Initiative (QBI). This one-year contract extension will support Xanadu's hardware and software development, particularly for its fault-tolerant photonic architecture and the PennyLane open-source quantum software framework. The funding aims to accelerate the development of practical, fault-tolerant quantum computing for various industrial and government applications. The post Xanadu Secures Up to $10 Million in Additional DARPA Funding Under QBI Program appeared first on Quantum Computing Report .

Insider Brief NVIDIA simulated a 104-qubit fault-tolerant quantum processor on Europe’s JUPITER supercomputer to evaluate magic-state cultivation under realistic hardware noise. The approach studied could reduce the qubits needed to produce magic states by 90% compared with previous methods, according to NVIDIA. The simulation used 8,192 GPUs and NVIDIA’s quantum computing software to help researchers assess processor designs before building hardware. PRESS RELEASE &#8212; NVIDIA today announced a record-breaking quantum computing simulation on JUPITER, Europe’s first exascale supercomputer, allowing researchers to fully explore and validate magic state cultivation — a leading approach to fault-tolerant quantum computing that requires 90% fewer qubits than previous methods. Running on a system of NVIDIA GH200 superchips at Jülich Supercomputing Centre, the 104-qubit simulation is the largest comprehensive simulation of a fault-tolerant quantum processor to date, modeling how a realistic quantum processor performs fault-tolerant computation at record scale. That level of fidelity gives researchers the data and tools needed to predict the performance of future designs before they are built — reducing reliance on hardware trial and error, and accelerating the path to useful quantum applications in fields like drug discovery, financial modeling and materials science. “Useful quantum computing will require fantastically complex, fault-tolerant systems — and understanding how they behave at scale is essential to building them,” said Jensen Huang, founder and CEO of NVIDIA. “Our results from Jülich show how quantum processors and GPU supercomputers can work together to tackle research that would otherwise be out of reach — accelerating the discovery of transformative quantum applications.” “Europe’s investment in JUPITER gives researchers the ability to investigate questions that were previously beyond reach,” said Kristel Michielsen, director of the Jülich Supercomputing

Podcast with Joel Van Dyk, a physicist turned Wall Street cybersecurity veteran, about the quantum threat to cryptography and what organizations should be doing right now to prepare. The post Podcast with Joel Van Dyk, CTO/CISO and Co-Founder of Done. Quantum Security Limited appeared first on Quantum Computing Report .

FlipFlop Tuoyuan, a Chinese quantum hardware startup, has secured over $14 million in early-stage funding to develop neutral-atom quantum processing units. Founded in July 2026 by Dr. Qiao Mu, the company aims to build a 100-logical-qubit fault-tolerant quantum computer and utilize AI for experimental design and hardware control. The post Chinese Startup FlipFlop Tuoyuan Emerges with Major VC Backing for 100-Logical-Qubit Neutral-Atom Systems appeared first on Quantum Computing Report .

The UK government and UK Research and Innovation (UKRI) have announced a £78 million (approximately $103.8 million USD) funding package to advance quantum sensing, networking, and workforce development. This initiative, part of the National Quantum Strategy, includes grants for commercial applications, supply-chain development, and an expansion of the QuEST Apprentices Programme. An additional £17 million has been allocated for integrating AI and high-performance computing with quantum platforms, aiming to solidify the UK's global leadership in quantum technologies. The post UK Government and UKRI Unveil £78M ($103.8M USD) Quantum Commercialization, Networking, and Skills Package appeared first on Quantum Computing Report .

Insider Brief Researchers developed an algorithm that allows standard computers to simulate photonic quantum devices using about 5% of the computing power previously required, according to the team. In tests involving Gaussian boson sampling, classical computers using the algorithm matched or exceeded the performance of some current quantum devices. The team is working to scale up the algorithm to support larger simulations that could help researchers assess current devices and design improved photonic quantum computers. PRESS RELEASE &#8212; Researchers have developed an algorithm that enables off-the-shelf computers to run quantum simulations previously only possible using the world’s most powerful supercomputers. It means the simulations can be run using around five percent of the computing power previously needed to perform them with a supercomputer, the team says. Quantum experiments The advance could make it cheaper and easier to run experiments vital for understanding the limitations of current quantum computers and informing the design of improved devices, experts say.&nbsp; Quantum computers could, in theory, perform calculations far beyond the capabilities of even the most advanced supercomputers, but current devices are small and error-prone, hindering their performance.&nbsp; Key to informing the creation of bigger, more reliable quantum computers is the development of algorithms to simulate how devices might work in reality.&nbsp; However, running these simulations has until now required vast amounts of computing power available at only a handful of facilities worldwide.&nbsp; Light-based technology The new algorithm was developed by a team led by scientists at Edinburgh and EPCC, the UK&#8217;s first National Supercomputing Centre, which is part of the University. The work could aid the development of light-based quantum devices, one of several branches of current quantum research by academics and industry, the team says. Computing power For the first

Insider Brief UK Research and Innovation (UKRI) has announced £50 million for UK quantum technology projects, alongside separate funding for quantum networking infrastructure and workforce training. The funded projects include MoniRail &#8216;s quantum railway monitoring system, Siloton &#8216;s handheld quantum eye scanner and ColdQuanta UK&#8217;s compact quantum radio system for signal detection and navigation. UKRI is also allocating £20 million to quantum networking businesses and expanding its QuEST Apprentices Programme with £8 million to support training for quantum and engineering roles. A share of £50 million is going to British businesses developing quantum technologies for uses that include keeping railways running, shortening eye scan waits and maintaining military connectivity, UKRI said. The money forms part of a new government package. According to UKRI , the package is delivered through its Quantum Technologies Priority Programme, as part of its Industrial Strategy programme The funding is aimed at companies building next-generation systems that could outperform current technology in critical areas. Projects Named Among the winning projects, as listed by UKRI: MoniRail , based in the West Midlands, is leading a quantum monitoring system that could locate faults in railway tracks and signalling equipment in places GPS cannot reach. UKRI said this would let track staff respond to problems as they arise and spare commuters last-minute delays. Siloton , based in Bristol, is developing a handheld quantum eye scanner. UKRI described it as designed to make advanced eye diagnostics available outside specialist hospitals through smaller, more accessible devices, and said it will improve access to care for patients nationwide. ColdQuanta UK, based in Oxfordshire, is being supported to develop a compact, mobile quantum radio system able to locate signals with high accuracy. According to UKRI, it could assist military operational intelligence, improve the resil

Large language models (LLMs) can generate quantum programs, but reliable evaluation remains difficult because benchmarks differ in task composition, scoring, and failure handling. We evaluate 15 hosted frontier, open-weight, quantum-specialized, and retrieval-augmented models on five quantum code-generation suites (530 tasks), plus 10 models on our new QuantumBenchEval (QBE) benchmark (96 tasks across six topics). We report bootstrap confidence intervals, multiplicity-adjusted paired comparisons, and audits of output validity and evaluator behavior. QiskitHumanEval-Standard approaches saturation (98.7% pass@1), while its Hard variant retains headroom (63.8%). None of the five top-two comparisons across primary suites remains significant after multiple-comparison correction. Evaluator design substantially changes scores: removing checks for unspecified quantities raises GPT-6 Astra's QBE pass@1 from 0% to 94.1% (T1) and from 1.2% to 92.9% (T6), without changing model outputs. We identify 17 QuanBench-117 tasks with shared failures linked to benchmark-owned imports. Controlled probes also reveal unexecuted unit tests, leakage of canonical functions into candidate execution, and reference imports that block otherwise valid candidates. These defects can produce both false failures and false passes, so historical QuanBench results require revalidation under an isolated evaluator. Overall, leaderboard scores alone do not adequately characterize progress in quantum code generation. We release our harness, per-sample results, and audit artifacts and recommend validating evaluators, isolating candidate code, and reporting uncertainty and output validity.

We perform a phenomenological study of non-classical correlations in the mixed-dimensional qubit-qutrit system realized by leading order $pp\to tW$ production at $\sqrt{s}=13$ TeV in the leptonic final state. The two missing neutrinos are reconstructed with conditional normalizing flows trained on simulated detector-level objects, and the joint spin density matrix $ρ_{tW}\in\mathcal{H}_2\otimes\mathcal{H}_3$ is obtained in a generalized Bloch representation from the angular distributions of the leptonic decay products. Non-classical correlations are quantified using the Peres--Horodecki negativity and geometric quantum discord. We quantify the correlations at different region of $m_{tW}$ at the reconstruction level within the Standard Model and the impact of two reducible backgrounds viz. $t\bar{t}$ and $WWj$ processes, tagged using boosted decision trees. We further study the behavior of correlations in presence of anomalous chromomagnetic and chromoelectric dipole moments of the top quark. The sensitivity reach of the quantum observables along with polarization and spin correlation parameters are reported for current LHC and future HL-LHC scenario.

Provided a maximally entangled state vector in ${\mathcal{H}}\otimes{\mathcal{H}}$, the Choi-Jamiolkowski isomorphism of quantum information theory (or channel/state duality) produces a mapping of ${\mathsf CP}({\mathcal{H}},{\mathcal{K}})$ (completely positive maps of density operators on ${\mathcal{H}}$ tothose on ${\mathcal{K}}$) onto the density operators on ${\mathcal{K}}\otimes{\mathcal{H}}$, which extends to a unitary map. Here, ${\mathcal{H}}$ and ${\mathcal{K}}$ are {finite-dimensional} Hilbert spaces.The nature of this construction, the form of the associated formulas, and the possibility of versions which do not require an entangled vector seed, are illuminated from the perspective of {naturality}, in the sense of Eilenberg and MacLane.There is a unique such correspondence (``Choi map'') natural in both ${\mathcal{H}}$ and ${\mathcal{K}}$ which produces density operators on either ${\mathsf L}({\mathcal{H}},{\mathcal{K}})$ (Hilbert-Schmidt inner product) or ${\mathcal{K}}\otimes{\mathcal{H}}^*$ instead of ${\mathcal{K}}\otimes{\mathcal{H}}$. In particular, no entangled state input is required. There are no such binatural maps carried on ${\mathcal{K}}\otimes{\mathcal{H}}$, but those natural in only ${\mathcal{K}}$ are canonically associated with unitary maps ${\mathcal{H}}\rightarrow{\mathcal{H}}^*$ and derive from the binatural maps. The construction recovers the standard Choi-Jamiolkowski formulae and shows how they express naturality.

Quantum and physics-inspired solvers provide specialized sampling interfaces for Ising and quadratic unconstrained binary optimization models, but constrained optimization requires broader coordination and certification. This survey uses classical decomposition to analyze how such solvers can be integrated into hybrid quantum-classical algorithms. We distinguish formal decomposition, reformulation and reduction, and computational orchestration. For each interface, we ask what the transformation preserves, which assumptions make the outer method converge, and which certificates the implemented inner routine supplies. The central questions are whether that information meets the classical algorithm's requirements and whether hybridization improves solution quality or total cost enough to justify its coordination overhead. Benders decomposition, column generation, graph reduction, and copositive methods illustrate this distinction by separating heuristic proposals from classical certification. We also distinguish component effects within a fixed wrapper, reduction--solver interactions, and comparisons between complete quantum-enabled and classical systems. The analyzed studies provide conditional component benefits and favorable co-design evidence, but do not establish transferable end-to-end superiority over strong classical comparators. The resulting framework identifies opportunities for constraint programming and operations research in structure-preserving design, safeguarded hybrid algorithms, and controlled benchmarking.

Given an open quantum system $S$ with environment $E$, we establish a one-to-one correspondence between completely positive trace-preserving (CPTP) maps from $S$ to $E$ and assignment maps initializing the composite system $SE$ in a possibly correlated state prior to unitary evolution. We show that every possible joint state $ρ_{SE}$ can be realized by such assignment maps, which are inherently Hermiticity-preserving and trace-preserving (HPTP). While these maps sacrifice global positivity, we derive a simple necessary and sufficient condition for any local state of $S$ to belong to their domain of validity. Furthermore, we prove that the geometry of this domain is governed by the joint state assigned to the maximally mixed input, ensuring that a non-zero volume of admissible local states can readily coexist with initial system-environment entanglement. Finally, we provide an operational protocol for witnessing such limits of validity.

Debugging quantum programs remains challenging due to the nature of quantum measurement. As quantum algorithms and systems scale, it is increasingly crucial to develop rigorous debugging and verification approaches. Statistical assertion-based debugging validates quantum program behavior through repeated circuit execution and statistical hypothesis testing, but existing frameworks treat shot count as a fixed input parameter, leaving the problem of optimal shot allocation across multiple mid-circuit assertions unexplored. To improve debugging efficiency by making better use of given shot counts, this paper proposes and evaluates four shot allocation strategies within the QDB quantum debugger implemented within the CUDA-Q framework. These allocation approaches: equal split, static weight allocation, adaptive entropy routing, and sequential retirement, use statistical approaches to test whether qubits have expected state characteristics at different points in execution. We evaluate these allocation strategies on different circuits, under both noise-free and depolarizing noise conditions. We show how adaptive strategies use shots efficiently by concentrating them on assertions with high uncertainty. This substantially reduces total shot usage while maintaining comparable debugging confidence.

This article presents a Distributed Key Management System (DKMS) that provisions quantum-safe symmetric encryption keys to applications across a network. To overcome the distance and rate limitations inherent to Quantum Key Distribution (QKD), the architecture adopts a hybrid design: it utilizes multi-hop trusted relays for physical key transport, while applying an end-to-end Post-Quantum Cryptography (PQC) layer to ensure the relayed key material remains strictly protected from intermediate nodes. Because QKD transforms key generation into a scarce physical resource, managing unpredictable application demands poses a critical capacity allocation problem. The core contribution of this work is an SDN-driven control plane that globally orchestrates the network. Rather than relying on vulnerable hop-by-hop capacity reservations, a central controller simultaneously computes optimal filling rates and multipath routing for all per-peer key buffers. This global orchestration ensures that no application is starved and that all key buffers synchronize their filling processes. Evaluated on a Kubernetes-based digital twin across five distinct network topologies, the controller successfully filled all key buffers to capacity in under six minutes. Furthermore, under deliberately excessive demand, the network demonstrated graceful degradation, safely rejecting excess requests through controlled rate-limiting rather than experiencing catastrophic failure.

Vehicle-to-Everything (V2X) communications rely on elliptic-curve signatures that a quantum adversary breaks and on pseudonym certificates whose anonymity rests on rotation rate, not cryptography. This work presents qDGSP, a post-quantum V2X infrastructure: a hash-based dynamic group signature scheme (DGSP, over SPHINCS+ and WOTS+) distributed between a central controller and roadside verifiers. Group keys derive deterministically from quantum key distribution (QKD) seeds served over the ETSI GS QKD 014 interface, so no group-signature secret crosses the classical channel. qDGSP-EA (Ephemeral Association) binds an ephemeral ML-DSA-65 key to one group signature per 5G cell: messages remain unlinkable across cells, linkable within one. On a testbed with emulated 5G links, median end-to-end latency stayed within the 100ms ETSI budget for every variant. The qDGSP-EA intra-cell DENM matched the NIST ML-DSA-65 baseline on the wire, and under load EA mode raised delivery from roughly 78% to 93%.

The total-current Hohenberg-Kohn conjecture asserts that the ground-state particle density and total current determine the scalar potential up to an additive constant and the vector potential up to a gauge transformation. We give three counterexamples for two spinless fermions in the physically relevant setting of three spatial dimensions. In each, a Hamiltonian $H^{v,\mathbf{A}}$ has a nondegenerate ground state with identically zero total current but nonzero magnetic field. Complex conjugation then yields a second Hamiltonian $H^{v,-\mathbf{A}}$, with the same scalar potential and interaction, whose ground state has the same density and the same zero current, while the magnetic field is reversed. The first two examples are noninteracting. One is explicit, with a smooth bounded vector potential and a Gaussian density. The other has smooth bounded scalar and vector potentials in the standard potential spaces. The third example has Coulomb repulsion with unit coupling, an isotropic harmonic scalar potential, and Dirac monopole fields of magnetic charge $\pm 1/2$. The monopole example uses vector potentials defined on separate spatial patches, since these fields are not curls of globally defined smooth vector potentials.

The three-tangle, $τ_3$, is a measure of genuine tripartite entanglement that distinguishes GHZ-type from W-type entanglement in pure three-qubit states. Here, we identify the statistically optimal one-sided four-copy detector of the three-tangle and study its implementation cost. The optimal detector has click probability $τ_3^2/48$, while previous four-copy constructions achieve $τ_3^2/256$ and therefore require asymptotically $16/3$ times as many experimental repetitions. Using the representation-theoretic structure of the problem, we construct an ancilla-free implementation of the optimal detector using 15 CNOT gates, together with an 11-CNOT detector with click probability $τ_3^2/96$. These results reveal a tradeoff between statistical efficiency and implementation cost, since reducing the number of repetitions requires increasingly expensive circuits. We then show that this tradeoff persists once the circuits are encoded. In a fully fault-tolerant setting, the increased click probability comes with a substantial non-Clifford synthesis cost, while an early fault-tolerant implementation based on $T$ gates and STAR rotations reduces this overhead at the expense of additional encoded resources. We quantify these costs using both the Steane and $[[8,3,2]]$ codes, providing explicit resource estimates for implementing the optimal detector across different computational regimes.

The ability to efficiently control optical quantum interference by the same device is a challenging task that promises to enable key operations in quantum information processing. Here, we tackle this problem by presenting a composite quantum plasmonic metasurface operating as an ultrathin non-unitary beamsplitter capable of achieving both single photon bosonic bunching and fermionic anti-bunching interference just by varying the incident photons frequency or changing the design dimensions. The presented metasurface combines a plasmonic grating corrugated by periodic nanoslits that can achieve extraordinary optical transmission with additional nanostripes on top forming nanocavities characterized by localized gap plasmon resonances. The photon-photon interactions are analyzed based on calculating the quantum coalescence metric which accurately portrays the obtained bunching or anti-bunching quantum interference. The presented quantum interference operation is applicable to both fundamental non-classical light interactions and in the design of more applied quantum optical logic gates used in quantum computing and communications.

Rare-earth molecular complexes are attracting increasing interest for quantum information applications because of their structural flexibility and chemical tunability. Here, we compare the cryogenic optical properties of Er$^{3+}$, Tm$^{3+}$, and Eu$^{3+}$ complexes in the same ligand environment. Optical spectroscopy shows differing behavior across the three systems: spectral hole burning is observed in the Eu$^{3+}$ complex, whereas no measurable hole is detected in the Er$^{3+}$ and Tm$^{3+}$ complexes. We measure laser-induced local heating and rethermalization in the Er$^{3+}$ and Tm$^{3+}$ powder-like samples, observing strong local heating and slow thermal relaxation in the cold-plate cryostat. The recovery occurs over several seconds and, for some Er$^{3+}$ excitation conditions, extends over tens of seconds. The comparison across the three ions nevertheless suggests that heating alone is unlikely to account for the full contrast. Rather, the different behaviors of Eu$^{3+}$, Tm$^{3+}$, and Er$^{3+}$ point to ion-dependent relaxation and decoherence processes associated with their electronic level structure and coupling to the molecular environment. Temperature-dependent linewidth and line-shift measurements are further consistent with phonon-mediated broadening through coupling to crystal-field levels.

The methodology of non-Hermitian quantum mechanics is employed to parameterize the dynamics of coupled classical diffusion equations describing low- and high-energy quasiparticles in superconducting single-photon detectors in one to three spatial dimensions.

We study coherent two-terminal transport through a finite-width $d$-wave altermagnetic quantum ring with nonmagnetic leads. A confined Aharonov--Bohm flux remains exactly $h/e$ periodic and, in the symmetric one-mode geometry, produces an exact half-flux transmission zero. A perpendicular field shifts the interference pattern according to an effective area $A_{\rm eff}=1.0342\,πr_0^2$ and the altermagnetic splitting resolves the common zero into nearby spin-dependent nodes. Rotating the crystal reverses the transmitted spin, whereas the mirror orientation $θ_A=π/4$ is exactly spin degenerate. For a $50$~nm reference ring, sub-tesla fields yield windows with $|P_T|>0.99$, the most accessible of which requires a uniform field alone and no confined flux. Finite-bias, thermal, disorder, Zeeman, and spin-conserving voltage-probe calculations show that the polarization is appreciably more stable than individual coherent-resonance amplitudes. These results identify interference-node positions, flux periodicity, and crystal-controlled spin polarization as experimentally useful signatures of an altermagnetic mesoscopic interferometer.

Suspended carbon nanotubes provide a useful platform for studying controlled nanomechanical motion in regimes where environmental fluctuations, memory effects, and quantum coherence can all influence the dynamics. We model the fundamental flexural mode of a carbon nanotube driven by an atomic force microscope as a harmonic quantum Brownian oscillator subject to a prescribed classical force and coupled linearly to a thermal environment. Starting from the generalized Langevin equation, we formulate the reduced dynamics directly in phase space, where the Wigner function evolves through a Gaussian propagator determined by dissipative linear transport, a deterministic force-induced displacement, and bath-induced fluctuations. For a Drude memory kernel, the retarded response is expressed through the three roots of a characteristic cubic equation. In the classical-noise limit, the three independent entries of the finite-time covariance matrix reduce to explicit finite sums over these response poles, eliminating numerical double-time covariance integration. We extend the construction to the full quantum fluctuation spectrum, obtaining a thermal frequency series representation that retains zero-point and low-temperature fluctuations. For an initial two-packet superposition, we examine interference attenuation and the integrated negative part of the Wigner function, which provides a phase space measure of nonclassicality. These results provide an explicit analytical framework for finite-memory quantum Brownian motion of bound oscillators and a tractable phase space description of driven carbon nanotube dynamics relevant to future quantum state preparation and quantum tomography experiments.

A growing research community spanning quantum batteries, molecular and excitonic energy transport, polaritonics, quantum materials and nuclear control has begun to describe its work in terms of quantum energy or quantum energy science. What connects these otherwise disparate efforts is the deliberate use of quantum states, couplings, collective effects and engineered environments to control energetic states and pathways. A key difference from quantum information science is that the complete quantum state does not always need to be preserved; engineered dissipation or dephasing can even improve the desired outcome. We organize this emerging domain through a framework that connects mechanisms, functions, capabilities, and applications. We identify five elementary functions (Excite, Hold, Release, Transfer, and Transform) and examine the mechanisms that implement them. The same functions recur from the molecular to the nuclear scale, although their relative implementation difficulty can differ sharply. Moving toward technology, we highlight three engineering capabilities (Storage, Routing, and Conversion) through the performance metrics that matter for their applications. Stretch scenarios illustrate what performance targets could make these capabilities technologically consequential.

Collecting photons from quantum emitters remains a key limitation in light-matter interaction because conventional lenses collect light only from one direction. Here, we introduce a perfect light collector by inverse-designing a surrounding dielectric structure that encloses the emitter to increase photon-collection efficiency toward unity. Decomposing the device into several refractive interfaces enables emission collection from the full 4$π$ solid angle with adiabatic reshaping into a collimated beam. We experimentally demonstrate, in two dimensions, the ray bending that collimates omnidirectional emission. Our collector transforms current paradigms for highly efficient photon collection from narrowband, cavity-based techniques into experimentally robust, broadband, non-resonant dielectric devices.

Scalable superconducting quantum computation requires fast, high-fidelity readout. Currently, this is assisted through cryogenic amplification of the readout signal. In traditional dispersive readout schemes, the amplifiers that are used to provide high signal-to-noise ratio also generate thermal noise that can decohere the qubits, demanding additional ferrite-based isolators to suppress this noise. Here, we integrate a chip-scale microwave switch, the tunable inductive bridge, into the readout chain of a fixed-frequency transmon. Flux-pulsing the switch, such that it transmits only during the readout, did not make a discernable difference to qubit coherence, residual excited-state population, or readout fidelity metrics. By injecting broadband noise that mimics amplifier thermal photons, we show that the switch suppresses the resulting qubit dephasing by more than $30$~dB, consistent with its independently measured on-off ratio, establishing it as a potential chip-based integrated replacement for readout-chain isolators.

Recent quantum-oscillation measurements in rhombohedral graphene reveal an abrupt increase in the dominant frequency and the emergence of additional frequencies as the carrier density is lowered toward superconductivity. Noninteracting band models can account for multiple frequencies but do not explain the upward jump. We show that these features can arise from two competing fates of the inner hole pocket in an annular Fermi sea: collapse into a simply connected Fermi liquid or crystallization into an anticrystal, in which localized holes coexist with itinerant electrons. Pocket collapse contracts the outer Fermi contour at fixed density, whereas hole crystallization preserves a larger contour that supports magnetic-breakdown orbits. This contrast provides a possible explanation for the frequency jump, while additional reconstructed orbits produce a multitone spectrum. Our results support the anticrystal as a candidate normal state near superconductivity in rhombohedral graphene.

We study multi-invariants---a multi-partite generalization of Renyi entropies---of simple stabilizer states, for an arbitrary replica symmetry group. We develop a group theoretic technique for evaluating such invariants, which operates on the replica group and involves counting intersections among its cosets. Our techniques streamline the calculations of multi-invariants for graph states with two GHZ-like nodes and for certain generalizations thereof. The methodology developed here is most suitable when the quantum state is simple but flexibility over the replica group is desired.

Ternary layered transition metal dichalcogenides (TMDCs) offer high tunability and access to correlated and topological states. However, like the broader family of layered TMDCs, their properties are sensitive to stacking order and interlayer coupling. Here, we investigate the electronic structure and surface states of NbIrTe$_4$, a candidate Weyl semimetal in bulk, and predicted to be a quantum spin Hall insulator in monolayer form. Using scanning tunnelling microscopy (STM), angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT), we attribute the strong resonance in tunnelling spectroscopy located approximately 8 meV below the Fermi level to a surface-derived flat band which shows sensitivity to the local stacking order at the surface. In regions where the top layer is laterally shifted, tunnelling spectroscopy instead shows a gap-like feature with intensity near the Fermi level shifted in energy. Combining DFT and quasiparticle interference (QPI) measurements, we find this dramatic change in the spectroscopy in the vicinity of the quasi-1D flat-band surface state becomes dispersive due to a change in the spatial distribution of the density of states in the top two layers. These findings establish NbIrTe$_4$ as a platform where surface band dispersion can be effectively tuned through local structural manipulation.

Rényi multi-entropy extends the Rényi entropy to pure states of more than two parties. It is defined by a replica contraction at integer replica number $n$, and the multi-entropy is its $n\to1$ limit. In holography this limit is conjectured to compute the area of a minimal soap-film web in the bulk. Understanding multi-entropy for general states, however, is harder. Unlike the bipartite case, the replica contraction is not a moment of a density matrix, and the continuation to $n=1$ has to be found by other means. We study this problem for qubit graph states. We show that at every odd $n$ the contraction equals $2^{-k/2}$, where $k$ is a sum of ranks of matrices over a finite field, one row and one column per qubit. We define a class of graphs that we call collision-controlled, for which the rank sum is a polynomial in $n$. This class includes graphs without even cycles and all complete bipartite graphs. The natural polynomial $n \to 1$ continuation is a finite sum over partitions of the parties. While the Rényi multi-entropy is non-increasing under single-qubit Pauli measurements at every odd integer $n>1$, the continuation to $n=1$ is not. A $Z$ measurement on one qubit of an odd ring with $2r + 1 \geq 7$ qubits raises it from $(r+1)\log 2$ to $(2r-1) \log 2$. Thus the continuation is not an entanglement monotone.

In quantum optics and related fields, cavity quantum electrodynamics provides a powerful framework for modeling the low-energy properties of bound charges coupled to electromagnetic fields, using a minimal set of atomic levels and isolated photonic modes. Here, we develop a similar framework for non-Abelian gauge theories, focusing on the pure-gauge dynamics of SU(2) fields as the conceptually simplest example. Starting from the corresponding Yang-Mills Lagrangian, we derive an SU(2) cavity Hamiltonian in the Coulomb gauge, represented in terms of only three localized bosonic modes. Unlike its non-interacting electromagnetic counterpart, this model exhibits a nontrivial excitation spectrum featuring bound composite gauge particles ('glueballs') as the lowest-energy configurations. We extend this framework to one-dimensional arrays of coupled SU(2) cavities and discuss the driven excitation of a glueball condensate and the clustering of multi-glueball states as two elementary interaction-induced processes in these models. These examples offer a glimpse into the multitude of novel many-body phenomena that arise within this cavity SU(2) framework and we show how this physics at the interface between particle physics and quantum optics can be experimentally explored using state-of-the-art superconducting quantum circuits.

Understanding how photon loss changes the classical complexity of BosonSampling is central to assessing the robustness of near-term photonic quantum advantage. In this work, we present a polynomial-time classical simulation algorithm for lossy BosonSampling that applies whenever a constant fraction of the input photons survives. We consider the standard fixed-loss model, where $N$ input photons propagate through an $M$-mode interferometer and exactly $N-n$ photons are lost uniformly at random, leaving $n$ surviving photons at the output. For any constant surviving fraction $n/N\in(0,1)$, the algorithm samples from a distribution within total variation distance $\varepsilon$ of the fixed-loss BosonSampling distribution with probability at least $1-δ$ over Haar-random interferometers, in time $\operatorname{poly}(M,N,\varepsilon^{-1},δ^{-1})$. We further extend the fixed-loss analysis to the uniform-transmission-loss model and obtain analogous polynomial-time simulability for any fixed transmission rate $η\in(0,1)$. These results substantially extend the known provably simulable regime of $n=O(\sqrt{\varepsilon N})$ surviving photons or $η=O(\sqrt{\varepsilon/N})$ transmission rate, and demonstrate that even the experimentally relevant linear-survival regime can admit efficient classical simulation under the conditions considered here.

Hidden-order phases elude the conventional Ginzburg-Landau framework: although they spontaneously break symmetry, their order remains invisible to standard local two-point correlators. Instead, they are typically characterized by nonlocal (string) order parameters and are believed to underlie a range of exotic quantum states, such as symmetry-protected topological (SPT) phases. While hidden correlations have previously been detected through nonlocal observables in quantum gas microscope experiments, in realistic solid-state systems multipoint observables are typically inaccessible and the signatures of hidden order remain largely unexplored. In this work, we show that hidden order in doped spin chains can be directly probed through dynamical two-point response functions measurable by resonant inelastic X-ray scattering (RIXS) and neutron scattering. Focusing on a minimal model, we numerically identify clear spectral fingerprints of both the hidden-order phase, its associated hidden quantum critical point as well as a specific group of gapless SPT phases. Complementing our numerical results with analytical insights, we uncover the microscopic origin of these spectral signatures and demonstrate how they emerge from the interplay between spin and charge degrees of freedom. Together, our results establish spectroscopy as a practical probe of hidden order and gapless SPT phases and provide a unified understanding of the low-energy physics governing these unconventional quantum phases.

The quantum Fisher matrix and geometric tensor are powerful tools for quantifying the nature of quantum systems. Unfortunately, the formalism needed to compute these quantities is opaque and has limited the development of physical intuition for their behavior, even in the ground state. For quantum systems with continuous symmetries, we know the ground state can be understood in a model-independent and intuitive way from the correlation functions of conserved currents and charges. In this paper, we demonstrate an equivalence between the quantum Fisher matrix associated with the ground states of systems with continuous symmetries and the Nambu-Goldstone. bosons produced by broken generators. We will show that the information metric defined by the Fisher matrix is the same as the Zamolodchikov metric that defines the coset space of the system. Next we show that the Uhlmann curvature associated with multi-parameter estimation is the same as the charge density matrix that defines the difference between type-A and type-B Nambu-Goldstone bosons. We demonstrate these connections in several examples and discuss the generalization to finite temperature.

The ability to assemble and reconfigure individual atoms is central to performing quantum science using optical tweezer arrays. Here, we demonstrate parallel omnidirectional atom transport and rearrangement using dynamic holograms generated by a single kilohertz-rate spatial light modulator. By carefully characterizing survival and heating, we show that atoms remain confined even when successive holograms are commanded before the liquid crystal has settled, enabling significantly faster transport. To generate holograms in real time, we develop and implement a warm-start, weighted Gerchberg-Saxton algorithm that achieves performance comparable to neural-network methods without requiring any training. Combining these techniques, we assemble ytterbium atoms into a 2078-site kagome lattice with 99.0% mean filling. In addition, we demonstrate parallel transport between array layers, combining axial and transverse motion to reconfigure atoms in three dimensions. Our approach is readily adaptable to existing tweezer platforms and provides a method for large-scale SLM-based atom assembly as well as programmable three-dimensional control.

Two-dimensional layers coupled by position-dependent interlayer tunnelling host a layer pseudo-spin whose polarization is a controllable internal degree of freedom. We introduce the quantum geometry of this layer pseudo-spin: a mixed tensor formed from the interband Berry connection and the layer matrix element, which governs the response to an oscillating in-plane electric field. Because the layer pseudo-spin is an Ising-type scalar invariant under threefold rotation, its selection rules differ from those of a pseudovector spin. In a minimal two-band model, the layer-pseudo-spin quantum metric and Zeeman--Berry curvature are nonzero, while their zone integrals vanish. An in-plane drive therefore leaves the spatially averaged polarization unchanged at linear order but imprints a moiré-periodic intracell pattern, directly imageable by layer-resolved tunnelling. For twisted MoTe$_2$ bilayer, we quantify the local dipole modulation and identify the rectified, helicity-odd, and third-harmonic channels through which a net response appears at higher order.

We show that quantum systems on non-amenable lattices, whose boundaries constitute an extensive fraction of the system, host novel forms of bulk ordering with no Euclidean counterpart. Combining boundary-retaining iDMRG with an exact symmetry-fixing duality, we investigate $p<5$ state clock models on the coordination-3 infinite Cayley tree. We find that between the ordered and disordered phases lies an emergent intermediate phase with bulk order induced by an arbitrarily weak boundary field rather than by conventional spontaneous symmetry-breaking. This establishes boundary-sensitive order as a distinct quantum ordering mechanism defying Landau's spontaneous symmetry-breaking paradigm. The intermediate phase realizes a bulk-boundary correspondence in which the unpolarized boundary selects a specific ordered bulk state.

We develop quantum algorithms for optimal control over a prescribed finite time interval (finite horizon), focusing on continuous-time linear-quadratic regulation (LQR). This foundational control problem often requires solving a nonlinear matrix Riccati equation, which can be costly for large systems and long control durations on conventional classical solvers. We instead work directly with the state-costate optimality equations, reformulating the LQR problem as a multiple-shooting linear system. Importantly, we prove a condition-number bound for the system that is independent of the horizon, under stabilizability and detectability assumptions. By incorporating the initial and final conditions into a single linear system, we can solve the subsequent linear system more efficiently with a quantum linear systems subroutine. For a given initial state, our quantum algorithms return classical estimates of the optimal cost and the optimal control inputs at a selected time, without constructing a Riccati solution operator. Given sparse-matrix block-encodings, an initial-state preparation oracle and a fixed number of control inputs, the query and gate complexities scale polylogarithmically with system size and control duration, provided that sparsity, relevant norms, and stability parameters are bounded. The dependence on the target error is inverse-linear up to logarithmic factors. We establish the required bounds uniformly in system size and duration for a family of damped mass-spring chains with two endpoint controls. Numerical experiments support the analysis.

Machine learning is widely regarded as a promising application in which quantum computing could offer a computational advantage. However, general quantum machine learning models with provable guarantees on performance, trainability, and efficient inference remain limited. In this work, we introduce quantum Hamiltonian embeddings, a supervised learning framework in which a classical training dataset is encoded into a single effective, parameterized Hamiltonian. Training optimizes the parameters of this data-dependent Hamiltonian, whose approximate ground state defines the classification rule. Once the ground state has been approximated using a quantum algorithm, inference can be performed either classically using a classical representation of the learned state, or with a quantum representation of the state. We establish efficient methods for gradient estimation and prove favorable generalization guarantees. Furthermore, under standard cryptographic assumptions, we show that Hamiltonian embeddings can realize hypothesis functions beyond the reach of efficient classical algorithms. We then demonstrate the framework at scale on IBM Heron processors using a standard benchmark dataset. Together, these results establish Hamiltonian embeddings as a new framework for quantum machine learning, combining theoretical guarantees with a path for experimental investigations at scale on quantum hardware.

Counterdiabatic (CD) driving suppresses the excitations of fast protocols by adding an auxiliary Hamiltonian, but in many-body and topological systems the exact CD term is generally non-local and multi-body. We study this obstruction for Thouless pumping in the Rice-Mele model, first without and then with interactions. For noninteracting fermions, the exact CD term of the pump is non-local, but the variational framework of Sels and Polkovnikov yields accurate nearest-neighbor approximations. For the spinful Rice-Mele chain with onsite and nearest-neighbor repulsion, in the regime where the competition of the two interactions stabilizes quantized pumping, this approach fails: the infinite-temperature variational action only penalizes the CD amplitudes, and the resulting two-parameter nearest-neighbor term does not prevent the pump from breaking down when the cycle time is reduced from $50/t$ to $2/t$. We trace the failure to the structure of the exact many-body gauge potential, whose amplitude for each hop depends on the interaction energy that the hop costs. Resolving the nearest-neighbor currents by this energy, and fixing the coefficients with a ground-state-weighted action, gives a local ansatz with 14 coefficients that keeps the interacting pump quantized for cycle times $T=2/t$ and $T=1/t$, with an accuracy per site that does not degrade between rings of 8 and 12 sites.

Correlated decoding improves matching and clustering surface-code decoders by reweighting one decoding subgraph conditioned on the other's correction. We show that standard reweighting can cause correlated decoders to fail on size-$(d-1)/2$ fault configurations that a distance-$d$ code should correct, reducing error suppression deep below threshold. Under circuit-level noise, a single first-pass edge can discount several correlated edges, even though their joint occurrence requires additional independent faults, so the decoder favors an over-discounted correction. Regularizing the reweighting rule restores the nominal distance scaling and a clear correlated-decoding advantage.

We benchmark the Iterative Redecode Scheme (IRS) on fast transversal Clifford circuits, achieving high-accuracy correlated decoding using local memory-style detectors and decoders. On a deep random Clifford benchmark, IRS yields approximately $4\times$ lower logical failure rates than the ghost protocol at $d=11$ with matched buffers, and $15\times$ lower rates than logical observable matching (LOM). In three-block GHZ preparation, IRS achieves $2\times$ lower logical error rates than reliable logical Pauli-product decoding with matched initialisation, improving to $25\times$ at $d=19$ with $\lceil d/2\rceil$ full initialisation rounds. We place IRS, which builds on Wan et al.'s scheme, within a broader propagation-assisted local (PAL) framework, where local decoders exchange messages rather than decoding a global hypergraph. IRS alternates local minimum-weight perfect matching (MWPM) on memory-equivalent detector error models (DEMs) with Pauli-frame propagation and detector updates across transversal CNOT layers, seeking local error estimates consistent with the global detector record. Prior-informed DEMs account for probabilities of propagated errors missing from the memory-equivalent model, improving initial decoding and reducing logical error rates. Zero-weight physical Pauli mechanisms enable inference and propagation of initially indeterminate stabilizer outcomes. Error rates saturate after a few iterations even for deep, adversarial alternating-tCNOT circuits, allowing iteration caps with negligible loss of accuracy. We find syndrome-extraction buffers of order $\lfloor d/4\rfloor$ sufficient for distance-dependent error suppression in the demanding regimes studied. The approach extends to other local decoders and CSS codes; for repeated logical $S$ gates, IRS achieves approximately $4$ to $10\times$ lower logical error rates than LOM, depending on initialisation.

We determine the exact quantum communication and entanglement-distribution capacities of three fundamental bosonic channels, namely thermal loss, thermal amplification and additive Gaussian noise, assisted by operations that completely preserve positive partial transpose (PPT). These operations are more powerful than local operations and classical communication (LOCC), but cannot generate distillable entanglement on their own. For thermal loss, the unconstrained capacity coincides with the Pirandola-Laurenza-Ottaviani-Banchi (PLOB) bound throughout the non-entanglement-breaking regime. The corresponding upper bounds are also attained for thermal amplification and additive noise. We extend these results to energy-constrained communication, establishing exact capacities for all three channels at every prescribed mean input energy. Our results solve a class of bosonic capacity problems under PPT assistance and establish exact benchmarks for determining whether the same communication rates can be achieved via LOCC alone.

We derive a general Gorini-Kossakowski-Lindblad-Sudarshan master equation for two co-located, uniformly accelerated two-level detectors weakly coupled to scalar fields in the Minkowski vacuum, retaining coherent and dissipative contributions for arbitrary orientations, field masses, and spacetime dimensions. For equal orientations, we determine stationary states and their entanglement for two couplings to massless fields in four dimensions: symmetric coupling yields acceleration-dependent concurrence, whereas rotating-wave coupling gives acceleration-independent concurrence.

We investigate quantum-state texture during the thermal relaxation of an anisotropic spin-$1/2$ Heisenberg dimer subject to a longitudinal magnetic field and a Dzyaloshinskii-Moriya (DM) interaction. Starting from local transverse and longitudinal couplings to a bosonic bath, we construct a global weak-coupling Lindblad equation, identify its transition channels, and discuss the applicability and limitations of the secular approximation. The Gibbs state is obtained explicitly in the local spin basis, revealing that the DM coupling controls both the modulus and phase of the single-excitation coherence by modifying the energy splitting and rotating the chiral phase. For heating and cooling protocols, we compare rugosity, fidelity-based texture, and trace-distance texture with coherence, vector spin chirality, and purity. The relaxation dynamics separates population thermalization from the decay and precession of deliberately prepared energy-basis coherence. Their combined contribution to local coherence produces DM-dependent texture overshoots and, during cooling, damped oscillations and sign changes of the coherence quadratures. These transients differ from the evolution of coherence magnitude and purity, while trace-distance texture weights them differently from the overlap-based quantifiers. Calculations at reduced dissipation preserve the texture maxima within the secular model. The results identify a phase-sensitive diagnostic of relaxation.

This is a set of detailed notes that are part of a Ph.D. Course on Quantum Control delivered at the Department of Chemistry of Seoul National University in 2014. Part of this course was also taught in the Department of Chemistry of the Friedrich Schiller University Jena. It focuses on quantum optimal control and quantum optimal control algorithms based on the gradient and extended gradient methods.

Accurate modelling of chemical reaction rates requires precise correlated energy differences. Quantum computing offers a potential route to their determination, but extracting energies from quantum-prepared states can demand prohibitive sampling. We demonstrate measurement-efficient correlated energy estimation using an electronically challenging H$_2$DBB--Ru model derived from a Ru-functionalized hafnium metal-organic framework relevant to radiodynamic and photodynamic therapies. The mixed estimator combines a quantum-prepared target with sparse multiconfiguration references and recovers ground-state corrections using magnitude-only compute-uncompute measurements. Analytical variance estimates predict 1.6 mHa precision with a few hundred shots, about 100 times fewer than the single-determinant formulation and three orders of magnitude fewer than optimized Hamiltonian-term sampling. With approximate targets, it reaches comparable accuracy using simpler state preparation than direct expectation-value estimation. Emulator and trapped-ion experiments on Quantinuum Helios validate the approach up to (10,10), including a 50-qubit circuit combining AI-assisted state preparation with error detection, providing a measurement-efficient route to correlated energy differences for challenging chemical problems.

Quantum annealing generally samples degenerate ground states with nonuniform probabilities. This unfair sampling depends on how the driver Hamiltonian couples these states near the end of annealing. For combinatorial optimization problems with a cardinality constraint, the penalty method and constrained quantum annealing (CQA) differ in these couplings. The transverse-field driver of the penalty method does not directly couple feasible ground states, whereas the fully connected XY driver of CQA couples pairs of them related by a single spin exchange. We investigate how this difference affects ground-state sampling, using closed-system simulations of random graph bipartitioning instances together with degenerate perturbation theory. For the instances studied, the conditional ground-state distribution of penalty-based quantum annealing approaches that of CQA at sufficiently large penalties and long annealing times. This convergence can be explained by the effective Hamiltonian of penalty-based quantum annealing, in which virtual single-spin flips to infeasible states generate a second-order interaction proportional to the CQA driver projected onto the feasible ground-state manifold, which is the leading term of the effective Hamiltonian of CQA. In the numerical simulations, the Jensen--Shannon divergence between the conditional ground-state distributions of penalty-based quantum annealing and CQA decreases approximately as the inverse square of the penalty-to-objective energy ratio, consistent with the perturbative analysis. This correspondence between the effective Hamiltonians extends to equal-weight fixed-magnetization constraints under the same perturbative conditions, providing a common mechanism for sampling bias in the two implementations.

We study tunneling between two identical, smooth, compactly supported potential wells in a constant perpendicular magnetic field, with the coupling and magnetic field fixed and the well separation tending to infinity. For a sufficiently small positive magnetic field, we prove lower bounds on the hopping coefficient and on the splitting of the two lowest eigenvalues outside a set of separations of density zero. If the well centers are separated by $2d_1$ and the magnetic field strength is $bλ$, the lower bounds have the form $e^{-bλd_1^2-Cd_1^{1+δ}}$ for every fixed $δ\in(0,1)$. No radial or reflection symmetry of the single-well potential is assumed. The proof combines the explicit Landau resolvent kernel with a complex analytic estimate for logarithmic averages of the hopping coefficient.

The primary pathway to the investigation of exceptional points (EPs) in open quantum systems has been the use of Markovian master equations. However, recently it has been realised that they can arise in settings that show non-Markovian behaviour. The main approach in this direction has been the use of pseudomodes, which allow the influence of a structured environment to be replaced by new damped auxiliary modes. In this work, we use a Heisenberg-equation approach which relies on the reaction-coordinate formalism to obtain exact analytical dynamics. First, we show how our method considerably simplifies the analysis compared to the use of master equations. Second, we utilise it to discuss non-Markovian revivals in systems with second and higher-order EPs, showing that the notion that EPs demarcate the onset of revivals is not generally true. We then utilise our results to discuss the dynamical effects of higher-order non-Markovian EPs, deriving bounds on the number of revivals and investigating enhanced asymptotic relaxation near higher-order EPs. Finally, we investigate non-Markovian EPs with engineered reservoirs and show how they can be utilised to control the rate of irreversible information loss.

Electrostatic gates on two-dimensional electron gases (2DEGs) in GaAs/AlGaAs heterostructures are essential for numerous studies of correlation driven phenomena, many performed within the fractional quantum Hall effect. However, the most commonly used type of gates, the metallic Schottky gate, has the propensity to adversely impact the electron mobility and suppress the fractional quantum Hall states. Here we demonstrate through commensurability oscillations under specially designed nanostructured superlattice gates, that strain effects are responsible for the mobility reduction. The experimental results agree well with COMSOL Multiphysics simulations. In a regular, unpatterned gate the disordered, granular nature of the metal film fills the same role as the superlattice in creating a strain field penetrating down to the 2DEG, as we show with a simplified model. These results will help in understanding, improving and finding novel methods to reduce strain-induced disorder in gated high-mobility 2DEGs.

An important aspect of many linear optical quantum computing architectures is probabilistically generating small dual-rail qubit entangled states, or seed states. While many schemes to achieve this have been discovered, attention has been primarily focused on minimizing input resources and maximizing success probability rather than establishing a detailed understanding of linear-optical error performance. In this work, we develop a framework for resolving sensitivities to physically distinct errors in linear optical state generation, allowing us to identify precise ways in which these errors affect the properties of the output state. We use this framework to identify seed state generators in which destructive many-photon interference prevents detector loss and detector noise from causing a falsely successful heralding event. We show that this effect suppresses errors, for example cutting the effective loss on the output of particular Bell state generators in half relative to a standard scheme. We also present a new Bell state generator in which both detector loss and detector noise do not affect the quality of the output Bell state to first order, and a 4GHZ generator with >75% higher success probability than a standard circuit. In addition we provide some useful identities, bounds and invariants for studying linear optical seed state generation.

The formulation of quantum measurements compatible with relativistic causality is obstructed by the tension between the locality of observable algebras and the dynamical state transformations induced by measurement processes. We develop a local measurement theory for quantum cellular automata, lattices of finite-dimensional quantum systems with a causal reversible dynamics evolving in discrete time steps. Measurement processes are described by localized completely positive maps and organized into operational measurement protocols, finite non-adaptive sequences of local instruments distributed across the causal cone induced by the automaton local dynamics. Each protocol induces an effective measurement on the initial time slice, whose support is constrained by the causal structure generated by the automaton. Non-local measurement effects therefore arise through causal propagation and composition of local operations, rather than from primitive non-local interventions or instantaneous collapse prescriptions. We establish the corresponding spatial support bounds and characterize the resulting measurement architecture. As an explicit example, we construct a two-step protocol for a one-dimensional nearest-neighbour qubit automaton which, for suitable automaton parameters, realizes a Bell-basis projective measurement on two neighbouring sites after coarse-graining of the local outcomes. Away from this point, the same protocol generates a continuous family of deformed Bell measurements whose entanglement and stabilizer Rényi non-classicality can be quantified explicitly. The framework thus provides a causally consistent operator-algebraic mechanism for synthesizing spatially extended quantum measurements from strictly local operations.

In hyperon-antihyperon production through electron-positron annihilation, quantum steering provides a stricter test of nonclassical spin correlations than entanglement. We determine when steering survives angular averaging and optimize angular selections to reduce the sample size needed to resolve it. In the specified production-frame spin convention, we show that windows symmetric about 90 degrees with even production-angle acceptance yield phase-independent Bell-diagonal states. Applying the necessary and sufficient criterion for steering under arbitrary dichotomic projective measurements determines the exact boundary for this family and reveals a steering region missed by the three-setting Cavalcanti-Jones-Wiseman-Reid (CJWR) criterion. For positive production parameters and uniform full-range acceptance, the steering threshold is $α\simeq0.36065$. We derive the covariance of weak-decay angular moments, construct fixed linear witnesses, and optimize the angular window. For $J/ψ\toΛ\barΛ$, steering survives full-range averaging. The statistical model predicts that, after separately optimizing the two angular selections at nominal $z=5$, the required full-range pair sample decreases from $8.61\times10^4$ for CJWR to $2.80\times10^4$ for the projective witness, a 67.4% reduction. This advantage persists under the production-acceptance and analyzing-power variations studied.

Rydberg atom arrays (RAA) have been advocated as a promising avenue for the quantum simulation of different exotic quantum states. Numerical predictions for the ground state properties of this experimental platform can, however, be challenging in two-dimensional setups. In particular, faithfully treating long-range interactions is often crucial for distinguishing the fate of competing phases, but it usually comes at considerable cost. Projected entangled-pair states (PEPS), optimized via a sampling-based approach, have been shown to deal with such terms on the same ground as shorter-range ones. In this work, we employ these tools to investigate debated physical questions in different frustrated geometries of RAA, from the emergence of spin-glass physics on the Kagomé lattice to topological order beyond the PXP model on the Ruby lattice. By that, we contribute to establishing PEPS as well-suited tools for creating digital twins of RAA experiments.

In the resource theory of superposition relative to linearly independent, nonorthogonal reference states, golden states are known for two reference states and for special overlap matrices, and all of them are maximally coherent in the Löwdin basis. We clarify what decides their existence and their Löwdin structure. The robustness and the geometric measure of superposition are maximized by the same states, which overlap equally with every reference state; their maximal values are set by the ground-state energy of a classical $XY$ model on the overlaps of the dual basis. For every overlap matrix, these states, and only these, are golden under the maximal superposition-free operations, but they need not be maximally coherent in the Löwdin basis. For the Kraus-type free operations, we prove a necessary and sufficient criterion, Gram majorization, for converting pure states into targets with nonzero coefficients; it reduces to majorization for orthonormal reference states. It shows that golden states of these operations must be maximally coherent in the Löwdin basis, but that this does not ensure their existence: three reference states that are not orthonormal admit a golden state if and only if their overlaps have a common modulus $s$ and their Bargmann phase $Φ$ obeys $s\geq2\cos[(π+|Φ|)/3]$. Equal-overlap states also yield a complete family of superposition witnesses in the Löwdin basis, which show that white noise on the span of the reference states is a resource unless these states are orthonormal.

The establishment of metrics and control of fundamental noise sources in quantum sensing is a long-standing goal in quantum science and technology. We report on the observation of polariton-mediated optical noise in a thermal Rydberg atom vapor and demonstrate its active control and suppression using a radio-frequency field in Rydberg electrometry. The noise exhibits structured amplification and reduction across the Rydberg electromagnetically induced transparency resonance. This reveals a nonlinear slow-light feedback mechanism in which the polariton medium stores and releases probe-field energy. We show that the reference radio-frequency field used in Rydberg heterodyne receivers can also tune the medium into an operating regime where high electromagnetic-field responsivity coincides with reduced optical noise. This operating-point control enables optimization of the electric-field sensitivity within the constraints imposed by Rydberg-polariton physics. These results establish polariton noise as a previously unrecognized intrinsic noise source in thermal Rydberg vapors and the corresponding control method as a crucial aspect of continued efforts to achieve fundamental sensitivity limits in Rydberg electrometry.

While quantum technologies are rapidly evolving, near-term applications heavily rely on hybrid quantum-classical paradigms. Among these, the classical shadows framework has gained a lot of traction, not only for quantum information science, but also for the development and verification of quantum hardware. It allows to efficiently classically estimate many properties of quantum states from randomized measurements alone, a task that is otherwise intractable due to the destructive nature of measurements in quantum systems. There are, however, many properties of interest that are, due to their very problem formulation, not efficiently estimable. In this work, we identify a computational kernel occurring in estimators of polynomial functions, a class of problems that are in general computationally difficult to solve. We show that this structure allows a row-wise partition that, together with a custom SIMD vectorization, enables massive parallelization and can reduce the computational cost significantly. We show applicability and scalability of the approach on different tasks, and our results showcase that the approach allows high sequential throughput and close-to-ideal parallel scaling. The work thus provides a new way of identifying and exploiting structure in classical shadow estimators, resulting in practical advantages on inherently difficult problems.

Fault-tolerant (FT) quantum computation offers a pathway to quantum advantage, but its realization is hindered by its significant overhead. The partially FT "STAR" architecture reduces the cost of universal computation at the price of relaxing FT requirements for non-Clifford operations, increasing exposure to hardware noise. Therefore, maximizing its performance and applicability demands careful co-design with the underlying hardware. In this work we investigate the co-design of the STAR architecture with neutral-atom platforms, connecting the underlying atomic physics to logical error modeling and application-level performance. At the physical level, we identify a favorable noise bias in $^{171}\mathrm{Yb}$ Rydberg gates, and show how it can be enhanced through error-selective pulse optimization. At the logical level, we identify an intrinsic error suppression mechanism, yielding vanishing logical coherent noise in leading order. Detailed circuit-level simulations of surface code implementations show more than an order of magnitude reduction in logical error relative to previous estimates. As a concrete target application, we focus on the Fermi-Hubbard model with periodic boundaries, for which we design a simulation circuit particularly suited to early implementations. We quantify the resource tradeoff of partially and fully FT approaches to gate synthesis, with the former showing approximately an order of magnitude reduction in state-injection depth, and an even larger reduction in Clifford resources. Comparing with classical and fully FT approaches, we identify regimes where partial fault tolerance provides both lower overheads and lower error rates. In our estimates, this is accessible with moderate error rates $p\sim 10^{-3}$ and a few thousand qubits, underlining that for these types of problems, partial FT approaches provide a compelling pathway to early quantum advantage.

The contextuality degree of a set of Pauli contexts is the least number of contexts that every noncontextual $\pm1$ assignment violates. For the four-qubit hyperbolic quadric $\mathcal{Q}^{+}(7,2)$, with $135$ points and $1575$ lines as contexts, Muller et al. conjectured from heuristic searches that the degree is $315$ and that the violated contexts of every optimal assignment form a dual polar space $DW(5,2)$. We prove both conjectures. The lower bound has a short proof by hand: every doily ($GQ(2,2)$) of the quadric contains ten Peres-Mermin grids covering each of its lines four times, so every assignment violates at least three of its fifteen lines, and averaging over the doilies gives $1575/5=315$. The equality case is local: an assignment is optimal exactly when it violates one ruling of one grid in every doily. Using this as a SAT encoding, we show that there are exactly $240$ optimal violated sets, one orbit of $\mathrm{O}^+(8,2)$, each isomorphic to $DW(5,2)$. The same argument gives the first lower bounds $\lceil L/5\rceil$ for all quadrics with $L$ lines in $N\ge4$ qubits. The degree theorem is kernel-checked in Lean 4, and the completeness of the enumeration is certified by a DRAT proof checked by the verified checker cake_lpr.

We examined the energy-momentum relationship of the valence band of Cu$_2$O, which has gained interest as an emerging solid host for giant Rydberg states. Our findings reveal a nonparabolic dispersion, described using the rest mass (0.570 times the free electron mass) and rescaled light speed ($1.6\times 10^5$ m/s), which draws parallels with relativistic theory for high-energy particles. We propose a straightforward expression for the bound-state energies of Rydberg excitons with finite quantum defects, whose energy scheme deviates from the hydrogenic series. This formulation identifies relativistic kinematics as the physical origin of quantum defects, offering a streamlined basis for future studies on complex many-body correlations.

Utility-scale quantum technologies will not only require a well-performing quantum platform, but also classical control hardware that is scalable, efficient, and meets the design requirements set by the quantum system of interest. One approach is the application of silicon CMOS technology, a highly scalable and mature technology, to design application-specific integrated circuits (ASIC) that are optimized for the quantum system. In this work, we present two-qubit control of electron and nuclear spins in NV centres in diamond, using a cryogenic CMOS qubit controller integrated with a diamond quantum device in a cryostat. Using Gate Set Tomography (GST) we characterize the performance of the single-qubit gates on both electron- and carbon nuclear spins, and analyze the limiting noise processes. We use dynamical decoupling to engineer a two-qubit gate, and estimate $F_\text{2q,avg} = 95(2)\%$ for the electron-nuclear two-qubit gate fidelity. Our demonstration of cryo-CMOS-driven two-qubit gates is a key step towards highly-integrated quantum devices based on colour centres.

The Parity Architecture was originally introduced in the context of quantum optimization algorithms to overcome hardware connectivity constraints. Here, we show that its benefits extend beyond this role by identifying specific parity transformations that enhance the success probability of the Quantum Approximate Optimization Algorithm (QAOA) for optimization problems defined on hardware-native and sparse graphs. Numerical simulations suggest that this enhancement originates from the higher-order operators introduced by the Parity representation, which accelerate the propagation of correlations across the physical device. We investigate this mechanism for the Signed Max-Cut problem on 3-regular graph instances and demonstrate its practical relevance on IBM Heron quantum processors. QAOA parameters are first classically optimized on small training instances containing up to 14 vertices and subsequently transferred to larger instances executed on quantum hardware. We consider Signed Max-Cut instances of up to 40 vertices and find that, together with an error mitigation technique, the parity-based QAOA identifies the optimal solutions for all the considered 40-vertex instances, whereas the conventional QAOA fails under the same conditions.

A linear potential gradient can strongly suppress quantum dynamics, while interactions can activate resonant many-body processes whose higher-order structure remains largely unexplored. Here we uncover a systematic hierarchy of high-order interaction--tilt resonances in an interacting Stark chain, where the resonance order counts the minimal number of elementary exchange steps involved. These resonances manifest as long-lived coherent oscillations with order-dependent timescales. By isolating individual resonant channels and developing a microscopic effective description, we connect these dynamical timescales to the underlying many-body exchange processes and reveal a pronounced dependence on the initial-state structure. Our results provide crucial insights into high-order many-body resonances and show how commensurate interaction-to-tilt ratios generate a hierarchy of parametrically slow coherent many-body dynamics.

We introduce squeezing-type lower bounds for a hierarchy of variance bounds under specific unbiasedness constraints, which generalizes the quantum Cramér-Rao bound. Our construction directly extends standard squeezing coefficients to the corresponding generalized metrological sensitivities while retaining their experimentally accessible structure. We show how observables maximizing these bounds can be identified analytically within families of accessible observables. If arbitrary observables are accessible, the optimized squeezing-type bound recovers the exact generalized metrological sensitivity. These bounds provide efficient and experimentally viable characterizations of generalized metrological sensitivities that are especially relevant in finite-shot scenarios and in the transition from local to global parameter estimation.

Compact quantum neural networks have been explored for cloud-cover parameterization, but their predictive value depends on how physical knowledge is incorporated and which classical models provide the reference. We investigate an offline residual formulation that retains a fitted \XR\ cloud-cover estimate and learns a correction to its logit in transformed target space. Using released ICON/DYAMOND-derived data, we compare ten model variants in six- and eight-input settings, with three matched replicates and 10,000 training samples per replicate. All quantum circuits use local Z readout and noiseless exact expectation values. Under a common 30-epoch protocol, residual prediction reduced physical-space test mean squared error relative to direct QNN prediction by 54.3\% and 38.8\% for six-input XYZ and ZZXY circuits, and by 49.2\% and 38.9\% for their eight-input versions. Residual QNNs also outperformed the selected compact residual multilayer perceptron in every paired replicate. A larger, longer-trained Grundner-Q1 adaptation nevertheless achieved lower error: residual Q1 reached mean MSEs of 0.00778 and 0.00791, compared with 0.01124 and 0.01082 for residual XYZ. The results support residual prediction for compact simulated QNNs within the tested budget and establish a clear boundary set by stronger classical references. They do not establish computational quantum advantage or online climate-model skill.

Universal behavior at continuous phase transitions is encoded in long-wavelength fixed-point theories controlled by dimensionality and symmetries. It is a central question for which systems this universal behavior and the underlying long-wavelength description can be captured by a noninteracting theory allowing for analytical and accurate predictions. In this work we provide a systematic procedure for obtaining the best noninteracting fermionic description of a quantum phase transition through fermionic Gaussian states. We demonstrate the performance of our procedure for the interacting long-range transverse-field Ising chain. This formulation reduces the problem to a self-consistent Euler equation that yields a critical line in close agreement with independent numerical benchmarks, while its singular momentum structure provides analytic predictions for continuously varying critical properties. Yet exact diagonalization shows that Gaussian-state fidelity to the exact ground state is poorest, and non-Gaussianity strongest, near the transition. Thus, accurate predictions for critical properties can emerge from the Gaussian variational description even where its microscopic wave-function approximation is weakest.

Quantum machine-learning (QML) models are increasingly considered for security applications, yet their adversarial robustness in malware analysis remains insufficiently understood. This paper presents Q-MALDetect, a hybrid convolutional and variational-quantum detector for byte-image representations of x86-64 Executable and Linkable Format (ELF) binaries, and evaluates it under feature-space and a range of Grad-CAM-guided, executable-aware evasion attacks. The model achieves 97.2% training accuracy, but its robustness deteriorates as attack strength increases, with the strongest evaluated feature-space attack reaching a 78.7% attack success rate (ASR). Among executable-aware attacks, Grad-CAM-guided no-operation (NOP) insertion produces the highest conditional ASR of 32.9%. Dynamic adversarial training is the most effective evaluated defense, reducing feature-space ASR to as low as 5.0%, executable-aware ASR to 7.7%, and the sequential-attack ASR to 34.0%. In contrast, convolutional-autoencoder preprocessing increases executable-aware ASR to 39.7%, coinciding with a rise in Grad-CAM attribution mass within the mutable .text region from 35.2% to 45.7%. Ablation results reveal no monotonic relationship between qubit count and robustness, while the encoding interface modifies the learned attack surface without neutralizing the strongest attack. These findings demonstrate that the effectiveness of attacks and defenses depends strongly on the perturbation constraints and evaluation conditions. Reliable deployment of QML malware detectors therefore requires assessment against both feature-space and executable-aware attacks rather than reliance on clean accuracy or generic denoising alone.

Mixed quantum states can exhibit unconventional forms of symmetry breaking without pure-state counterparts. A prominent example is strong-to-weak spontaneous symmetry breaking (SW-SSB), which cannot be diagnosed by observables linear in the density matrix. Here, we experimentally resolve finite-size critical signatures of SW-SSB transitions on a superconducting quantum processor. We develop a measurement protocol that combines quantum measurements with classical processing based on the known dephasing channel to reconstruct nonlinear mixed-state correlators. Using only two measurement settings, the protocol reconstructs fidelity, Rényi-2, and linear correlators, as well as string observables. Applying this approach to matrix-product states subjected to power-law-correlated dephasing, we observe finite-size crossings and scaling collapses in nonlinear correlators, accompanied by decaying linear correlations. We further map the estimated SW-SSB transition points across initial-state and channel parameters. Measurements of linear and Rényi-2 string observables further reveal signatures of mixed-state symmetry-protected topological (SPT) phases, with a nonlinear string-order crossover aligned with an independently estimated SW-SSB transition point. Our results establish a quantum-classical approach to probing SW-SSB critical behavior and mixed-state SPT order.

Fresh qubits, not size, set how long a noisy quantum system can remember. With $k$ input qubits reinitialized per time step, the longest memory any reservoir can attain under depolarizing noise is $\exp[Θ(k)]$ time steps, whatever its size, dynamics, and input encoding. A universal upper bound and an explicit reservoir that attains the exponential scaling establish this optimal resource law. The bound depends on the dynamics only through the entropy that fresh qubits remove per time step, so it holds for any Markovian noisy dynamics without feedback, including measurement-free error correction.

Sidewall morphology is a potentially important factor influencing superconducting qubit performance, yet its quantitative characterization remains challenging due to the absence of standardized measurement protocols. In this work, we develop a scanning probe microscopy-based measurement framework for the quantitative characterization of superconducting qubit sidewalls. The framework introduces a refined root mean square lateral sidewall roughness descriptor and a new curvature-equivalent radius for quantifying vertical sidewall morphology. The descriptors and measurement procedures are applied to different components of qubit devices, forming the basis of a proposed sidewall characterization protocol. This provides a foundation for quantitative comparisons of fabrication processes across laboratories, enabling future investigations of correlations between sidewall geometry and qubit performance.

Classical methods for computing quantum expectation values often propagate observables in the Heisenberg picture. To remain tractable, these methods rely on approximations that discard operator components during evolution. Yet the magnitude of these components alone does not determine the resulting expectation-value error, which also depends on their subsequent evolution and the input state. We develop \emph{generalized Pauli propagation}, a common algebraic framework encompassing Pauli propagation, Lie-algebraic simulation, and Krylov subspace methods. Using weighted commutator graphs, we derive exact identities that relate approximation errors to the signed contributions of omitted and discarded operator components. Our central result establishes \emph{delayed observability}, identifying conditions under which these contributions vanish at low orders in propagation time. We use this structure to develop finite-order error estimates and state-dependent selection rules. We further prove that retaining the symmetry-preserving part of a weak perturbation eliminates first-order expectation-value errors under suitable symmetry conditions. By revealing how approximation errors affect the desired expectation value, our framework provides a basis for more informative error analysis and the development of readout-aware simulation strategies.

A quantum walk is a mathematical model and a quantum version of a random walk. For the past two decades, it has been studied from mathematical and physical viewpoints. It has many desirable properties. This paper reevaluates quantum walk from a quantum mechanical perspective, as Feynman essentially proposed it as a toy model in his path integral method. Then we demonstrate that the quantum walk model exhibits both particle-like and wave-like properties by showing reflection and partial reflection as a particle and interference as a wave. In particular, for an initial state supported at two sites $\pm\ell$, we explicitly derive the weak limit distribution of the Hadamard walk and show that the Konno distribution is modulated by the interference factor $2\cos^2(\ell k(x))$. The resulting interference profile is reminiscent of far-field (Fraunhofer-type) diffraction.

Altermagnets are an emerging class of magnetic materials that exhibit characteristic features of both ferromagnets and antiferromagnets. Odd-wave magnets, where the momentum-dependent spin splitting follows an odd-parity form factor, provide a distinct platform for exploring unconventional magnetic and topological phenomena. In this work, we demonstrate light-induced topological phase transitions in odd-parity magnets driven by bicircular light. We show that a cascade of topological phase transitions occur as the relative amplitude ratio of the two beams is varied. These are accompanied by sharp changes of the quantum metric. We demonstrate that bicircular light unlocks nonlinear Hall responses arising from Berry curvature and quantum metric in irradiated odd-wave magnets, and formulate the underlying selection rules. Our results show that both the topology and the nonlinear responses in odd-parity magnets can be directly controlled by a bicircular drive.

The Renormalization Group (RG) establishes relations between effective descriptions of physical systems at different scales; in Hamiltonian RG, these relations induce a flow in the space of Hamiltonians. In direct correspondence, we design an RG framework for quantum control by constructing a flow in the space of time-dependent Hamiltonians. A prescribed control subspace, selected to contain only experimentally accessible terms, forms the fixed-point manifold, while the flow preserves the target unitary and monotonically reduces the Hamiltonian weight outside this subspace. Exploiting the freedom in constructing the flow, we introduce flow-equation engineering to enhance the versatility of the framework for diverse control problems, including time-periodic and open-interval smooth protocols with prescribed endpoints. We provide two disparate applications to exhibit the utility of our approach: (i) Nonperturbative Floquet engineering beyond the regime of validity of high-frequency expansions, which we demonstrate by constructing an implementable time-periodic protocol for the Haldane model; (ii) Accessible fast-forward driving from unit-fidelity counterdiabatic evolution, which we showcase for large transverse-field Ising chains away from the adiabatic regime by compressing the long-range multibody adiabatic gauge potential into the original time-dependent Ising control schedules. Our control RG framework reveals a unifying perspective on Hamiltonian engineering and unitary quantum control, and can serve as an organizing principle behind seemingly disparate nonequilibrium quantum dynamics.

We investigate open-system charging protocols for Rabi and Dicke quantum batteries under direct incoherent pumping. The charging dynamics follows a Lindblad master equation, while effective non-Hermitian generators describe the conditioned no-jump mechanism. For a single Rabi battery, this pumping suppresses coherent energy backflow, broadens the high-energy charging window, and improves robustness against both timing errors and detuning. At the selected Rabi operating points, pumping also increases ergotropy and the extractable fraction of the stored energy. For finite Dicke batteries, direct incoherent pumping likewise stabilizes the charging dynamics. Across the finite-size scan, the strongest pump considered improves the peak stored energy and ergotropy per cell and near-peak timing robustness relative to the Hermitian reference. The maximum average charging power also increases, although this metric includes pump-assisted jump contributions. Equal-input comparisons show that the relative performance of common-cavity Dicke and independent Rabi batteries varies with the pump-input bound. Taken together, these results show that direct incoherent pumping provides a route to stabilized charging in Rabi and finite Dicke quantum batteries.

Quantum communication networks promise information-theoretic security but this security collapses if intermediate relay nodes are compromised, a risk that grows sharply when compromised nodes cannot be identified. We address this twofold: first, we show that multi-path routing provides quantifiable protection against unidentified compromised nodes. Second, we provide a comprehensive statistical and graph-theoretic analysis of network and node security under compromise, covering full and partial node compromise, optimal placement of additional edges via an iterative method, and comparative hacking-probability analysis across network topologies. Together, these results identify the topology and multi-path routing strategy that most improves security for a given network. We apply this framework to quantum key distribution across multiple network topologies, demonstrating a scalable route to secure, reliable quantum communication under realistic, unidentified adversarial threats, without relying on quantum memory.

Distributing quantum circuits across a network of quantum devices is a recent approach to improve the scalability of quantum computation. Entangled pairs of qubits distributed across network nodes are used as a communication resource for executing inter-node (remote) gates. However, establishing these entanglement pairs incurs significant latency, and doing so during the circuit's execution may lead to the decoherence of logical qubits. Instead, it may be beneficial to distribute certain entanglement pairs before the circuit is executed. Thus, we consider the problem of distributing a quantum circuit across a quantum network containing some pre-distributed entanglement pairs and seek to minimize the execution time of the circuit. We address this problem in three steps. First, given the quantum network and (optionally) a probability distribution over training circuits, we determine a set of pre-distributed entanglement pairs under a specified budget. Second, we compute a qubit-to-memory allocation that minimizes the expected execution time given these pre-distributed resources. Finally, we identify any additional entanglement pairs required during execution, generate them concurrently, and execute the circuit gates. We evaluate our methods on a broad range of benchmark circuits.

Thermal light exhibits intensity fluctuations or photon bunching that has been used as a source of entropy or temporally correlated light. However, its low spectral density limits its use in practical applications like LIDAR. One method of remedying this is optical amplification to boost its brightness. In this paper, we show that the normalized second order coherence function $g^{(2)}(τ)$ of a thermal light source is preserved after amplification. We then use amplified thermal light to demonstrate a LIDAR raster scan of a building at 1.3 km with a depth resolution of 2 cm.

Light curves reveal stellar variability and support studies of stellar evolution and cosmic distances. Reliable classification is therefore important for large time-domain surveys. We present HyQ-LC for ten-class stellar light-curve classification using 359 handcrafted features and 633,034 training objects. The main model combines a window multilayer perceptron (MLP) backbone with a nine-qubit readout using amplitude encoding and angle re-uploading. Both this hybrid and its pure-MLP control have 44,238 parameters. On a shared 20,000-object test set, the hybrid has macro-averaged F1 (Macro-F1) point gains of 0.8276 and 1.2393 percentage points over the pure MLP on two fine-tuning seeds. A separate fixed-fusion configuration achieves slightly higher Macro-F1 but lower accuracy than approximately budget-matched LightGBM. Its positive class-level differences are concentrated in CEP, RRC, and ROT, while the full-budget LightGBM reference scores higher on both metrics. All circuits are simulated classically. The comparisons retain existing validation-selected checkpoints and use the same test objects, with features, predictions, and recomputation code publicly available. The results identify point-estimate improvements over the tested controls while leaving the specific contribution of the quantum branch unresolved.

We present a fully quantum theory of time-resolved transient absorption spectroscopy, providing a general framework for describing the linear response of a nonequilibrium target to quantum probe fields beyond the semiclassical approximation. We elucidate how quantum correlations between probe-field frequency modes couple to coherences in the target and derive a simple expression for computing the resulting spectroscopic signals. We identify conditions under which quantum light can modify transient absorption spectra beyond the limits achievable with classical fields. Our work establishes a theoretical foundation for exploiting quantum light in ultrafast spectroscopy and suggests new routes for resolving dynamics in matter on timescales shorter than the duration of the probe pulse.

Satellite-based quantum links are a promising enabler of long-distance entanglement distribution, overcoming the exponential losses of optical fibers. In uplink architectures, entangled photons are generated at ground stations and transmitted to orbiting satellites, reducing space-segment complexity but introducing significant atmospheric and geometric losses. Single-satellite dual-uplink configurations are additionally limited by the requirement of simultaneous visibility between both ground stations and the satellite. In this work, we investigate a dual-uplink dual-satellite network architecture and compare its performance with the single-satellite scheme under identical physical assumptions. The proposed topology introduces an inter-satellite link (ISL) that decouples the ground-station separation from the atmospheric uplink geometry. A realistic channel model is employed, incorporating geometric attenuation, atmospheric turbulence, background noise, and Bell-state measurement efficiency. The overall success probability and practical fidelity are evaluated as functions of satellite altitude and ground-station separation. Our results show that while the single-satellite configuration is suitable for regional-scale networks, it becomes infeasible for large separations due to geometric constraints. The proposed dual-satellite architecture mitigates this limitation and significantly extends the achievable communication distance, representing a key step toward scalable quantum internet infrastructures.

Controlling fermion parity in quantum-dot Josephson junctions (QDJJs) enables access to novel superconducting physics. While parity transitions are usually tuned electrically, we study phase-induced transitions in a strongly coupled QDJJ using the superconducting phase difference across the dot terminals, denoted by $φ$. We find that this phase allows control over the ground state parity, with parity transitions observed as the Andreev bound states (ABSs) energies crossing zero. These crossings occur near $φ= π$, and their behavior is in good correspondence to a simple model considering a single-level quantum dot proximitized by a superconductor. These results place phase-controlled QDJJ arrays as a promising platform for exploring exotic phenomena such as Majorana zero modes.

In an earlier work, we showed that, in the interaction-dominant setting, coupling the conjugate variables of a subsystem to distinct environment modes drives the subsystem to a maximally mixed state. Here, we extend the study to the full quadratic dynamics of a single-mode subsystem coupled to a two-mode environment, and identify the phase-space mechanism responsible for the asymptotic behavior. By tracking the exact reduced Weyl characteristic and Wigner functions, we demonstrate that they lose their dependence on local phase-space coordinates on every fixed compact region. In free-particle model, this happens for all values of coupling, whereas in the harmonic oscillator model, it happens above a critical value of the coupling. Under a finite-volume and momentum regularization, this behavior corresponds to the reduced subsystem approaching a maximally mixed state.

Accurately characterizing molecular properties and reactivity often requires electronic-structure calculations across an ensemble of molecular geometries. Quantum algorithms that process such ensembles coherently could address this challenge, but they require Hamiltonian block encoding circuits that combine advanced factorization techniques with sublinear scaling in ensemble size. Here, we introduce SVD-THC, which extends tensor hypercontraction to sets of Hamiltonians defined at different nuclear geometries through a singular value decomposition of the ensemble. We use SVD-THC to construct a single multiplexed block encoding circuit for all geometries in an ensemble. We then evaluate the approach on ensembles generated by varying internal rotational coordinates in 1-bromo-2-chloroethane as well as in glycine and alanine dipeptides, corresponding to established model systems for peptide conformational landscapes, with up to 5,184 geometries. Across several resolutions of the internal-coordinate grids, the Toffoli complexity of the resulting circuits grows only weakly with the number of geometries, changing by at most 12\% over grids that differ in size by up to 576$\times$. In an energy-thresholding circuit, this yields 35--200$\times$ fewer Toffoli gates than slicing together single-geometry block encodings. This approach could help make coherent processing of molecular geometry ensembles a useful primitive for fault-tolerant quantum computing.

The use of entanglement in sensing is often motivated by improved sensitivity arising from non-classical correlations among probes. For static signals, however, this quantum advantage in Ramsey spectroscopy with $N$ probes is known to be highly susceptible to dephasing, which severely limits the possible gain from entanglement. In contrast, we consider sensing of signals that vary in time. Considering the simplest example of dephasing by classical white noise, we show that entanglement allows a large increase in bandwidth when estimating the frequency components of a time-dependent signal. Without sacrificing any sensitivity, entanglement allows for an increase in bandwidth by a factor of $N$. Alternatively, when interrogation times are limited by the signal bandwidth rather than by dephasing, the average estimation uncertainty over a fixed bandwidth is reduced by a factor of $\sqrt{N}$ compared with separable states.

Quantum states are ultimately responsible for numerous counterintuitive phenomena that defy classical intuition. As the development of quantum technologies accelerates, our ability to harness these quantum resources becomes essential. This review addresses a fundamental question. How do we quantify the quantumness of a state, and which specific traits distinguish it from its classical counterparts? We examine quantumness through both theoretical and operational lenses, providing a clear framework for state characterization. Ultimately, we demonstrate that certifying quantumness is not just a theoretical exercise. It is a practical necessity for identifying, and realizing quantum advantage in real-world applications.

Plasma simulations for magnetic-confinement fusion (MCF) involve high-dimensional kinetic dynamics, strong nonlinear coupling, complex geometries, and multiscale spatiotemporal behavior, imposing severe computational bottlenecks. While quantum computing offers a potential alternative for accelerating plasma simulation problems, its practical advantage for fusion research has not yet been demonstrated. We review existing quantum computing studies across kinetic dynamics, wave interactions, equilibrium, and macroscopic stability, evaluating their hardware implementations and operational bottlenecks. Current studies remain largely restricted to linearized equations, reduced models, or isolated computational subroutines, leaving a substantial gap from realistic fusion simulations. We summarize key problem characteristics, including high dimensionality, structured dynamics, and measurement requirements, under which plasma applications are most likely to yield a quantum advantage. Guided by these considerations, we highlight potential approaches and present a roadmap toward practical quantum advantage of simulating plasma in MCF.

This paper is a non-planar counterpart of the author's earlier work on planar contact structures and topological quantum computation. On a planar page every branch point is paired by a liftable arc, and the pairing matches the Ising representation exactly, in that fixing the channels of the pairs already fixes the state. Here the page has genus g and connected binding, presented as a simple degree-three cover of the disk. Every maximal system of disjoint liftable arcs then has exactly g members and leaves two branch points unused, and the half-twist interchanging the two points is not liftable, although its cube is and lifts to the identity. Ising fusion does not see that leftover pair, determining its channel from the other g and acting there only by scalars, whereas Fibonacci fusion can leave the channel undetermined. The powers of the cube then act by ten distinct relative phases on a single joint eigenspace, while the Calabi-Yau Stein filling stays fixed. An integral residue criterion supplies the Calabi-Yau test, a factorization localized on a contact connected sum is automatically Calabi-Yau, and, unlike in the planar case, a Calabi-Yau factorization need not be the shortest.

Emerging quantum networks enable distributed quantum computing (DQC) by interconnecting modest, noisy quantum processors. However, practical deployments face tight memory budgets, probabilistic entanglement generation, and decoherence, all while serving multiple users. In realistic settings -- cloud execution, iterative/interactive workloads and concurrent jobs -- circuits do not arrive in a single batch but as a stream. This creates a fundamentally online problem: the system must react to stochastic arrivals, balance latency and throughput, and remain stable under varying loads without foresight of future jobs. We study Online Scheduling and Distribution of Quantum Circuits (OS-DQC) and formalize the online scheduling problem for quantum networks: circuits arrive over time and must be executed without knowledge of future arrivals. At each event time (arrival or completion), the system decides which waiting circuits to launch and how to place their qubits, while accounting for congestion from in-flight circuits and constraints due to finite memories and decoherence. The objective is to minimize the mean completion time and makespan under these physical and resource constraints.

Many quantum-information tasks can benefit from Gaussian quantum resources, while their fundamental performance limits are characterized by quantum information quantities. However, a unified perturbation theory for these quantities directly within the Gaussian-state formalism has been lacking. We develop such a theory for the von Neumann entropy, quantum relative entropy, quantum Chernoff quantity, and quantum fidelity, using perturbations of the moments of a reference Gaussian state. Using general Fréchet-derivative identities, we derive compact second-order expressions for reference-state covariance matrices whose symplectic eigenvalues are all greater than $1/2$. We also show that the perturbative quantum Chernoff quantity is maximized at its symmetric point, yielding the quantum Chernoff exponent (QCE). We further show that symplectic eigenvalues equal to 1/2 can lead to slower asymptotic vanishing, potentially improving the corresponding fundamental performance limits. For reference-state covariance matrices containing symplectic eigenvalues both equal to and greater than 1/2, we identify sufficient conditions under which the former determine the leading covariance-matrix contributions, allowing the remaining modes to be traced out without changing the leading-order asymptotic scaling or the coefficient. Applying the framework to quantum illumination and incoherent-light sub-Rayleigh object discrimination, we recover known asymptotic QCEs directly within the Gaussian-state formalism. In the latter problem, the slower asymptotic vanishing explains the known quadratic scaling of the QCE with the source separation.

The quantum phase of a multiparticle system has remained a long-standing mystery in quantum physics. The absence of a phase operator that faithfully represents this physical quantity has prevented the formulation of a meaningful uncertainty relation with particle number. Here, we resolve this problem by measuring, for the first time, the quantum phase of multiparticle systems containing up to fifteen particles. We achieve this through a new quantum state tomography scheme that combines homodyne interferometry with photon-number-resolving detection. This approach enables us to reconstruct complementary photon-number and phase representations and establish the corresponding number-phase uncertainty relation. Our measurements further provide access to the mutually unbiased basis of a multiparticle system, a fundamental resource for multiparticle quantum information processing. Furthermore, we report the spatially resolved characterization of the quantum phase. These results provide an operational framework for measuring quantum phase in multiparticle systems, with implications for fundamental quantum physics and scalable multiparticle quantum technologies.

Complex amplitudes can be simulated over real Hilbert spaces by adjoining a two-dimensional real/imaginary degree of freedom. In a multipartite program, however, one globally shared phase tag is not a locality-preserving program transformation: every party would have to act on the same auxiliary system. We recast the distributed real simulation of multipartite quantum mechanics as a syntax-directed compiler into a real misty-state intermediate language. For $n$ parties we give explicit phase-reference codewords $|0\rangle_{P_n}$ and $|1\rangle_{P_n}$ on $n$ local tags and prove that the same real operator $J=XZ$ on any single tag realizes the logical action of multiplication by $i$. If a complex party-local gate is $A=A_R+iA_I$, its real translation is \[ \widehat A_j=A_R\otimes I+A_I\otimes J_j, \] which acts only on party $j$'s data and local phase tag. We prove an intertwining theorem for arbitrary finite party-local pure-state circuits, exact preservation of computational-basis measurement probabilities, preservation of the run-time interaction graph, and one-rebit-per-party overhead. For the canonical three-party GHZ program, the translation lies entirely inside the ordinary black-and-white misty gate fragment: controlled-$J$ replaces the complex phase operation, while the invariant $J_jJ_k|0\rangle_P=-|0\rangle_P$ transfers the required branch sign. This yields a short correctness proof for all four promised GHZ inputs and explains the earlier 64-path cancellation calculation at a single logical phase-code boundary. We distinguish this program realification problem from the weaker task of finding any real strategy with the same correlations, and state precisely which parts are known real-Hilbert-space simulation and which parts belong to the misty-language compilation layer developed here.

We develop a systematic method to compute the subsystem fidelity and Rényi fidelity in two-dimensional conformal field theories (CFTs) from the operator product expansion of twist operators, and apply it to the subsystem quantum Bhattacharyya distance (BD) and Rényi-Bhattacharyya distance (RBD). We validate the method against exact results in the free massless fermion and boson theories, and then use it to compute the BD and RBD in holographic CFTs between two heavy primary states, between two thermal states, and between a heavy primary state and a thermal state. When the two states differ in their classical, order-$c$ data, the distances are of order $c$, and the states are distinguishable already at the level of classical gravity; when the leading data coincide, the distances are of order $1/c$ at every order of the short interval expansion, so that the distinguishability becomes a perturbative quantum gravity effect. For a heavy primary state and its thermal counterpart, the leading contribution to the BD appears at order $\ell^8$ and is of order $c^0$, whereas the RBD is generically of order $c$, in line with the earlier finding that a heavy primary state and a thermal state share the same order-$c$ entanglement entropy but have different order-$c$ Rényi entropies in the short interval expansion.

We study whether a quantum verifier can find a hidden quantum state by exchanging classical messages with an unbounded prover who knows the state. The verifier has access to a reflection oracle about the target. For a Haar-random $n$-qubit target, we prove that achieving constant average fidelity with the target requires $(q+1)^2(B+1)=Ω(2^n)$, where $q$ is the number of verifier queries and $B$ is the total prover-to-verifier communication. The bound allows arbitrary classical interaction and unrestricted computation between queries. Our proof extends the lower bound of Aaronson and Kuperberg from a single classical proof to an arbitrary classical interaction. As a result, we obtain a quantum-oracle separation of UniqueQMA from QCIP with polynomially many classical messages. In particular, we give a unitary oracle $\mathcal{U}$ such that there exists a language $L\in\mathrm{UniqueQMA}^{\mathcal{U}}$ but $L\notin\mathrm{QCIP}^{\mathcal{U}}$. We further give an oracle construction for a notion known as QMA-QCIP[2] gap problem. This gives average case hardness for a QMA language under classical access to a QCIP[2] decision oracle and is used in establishing negative results on witness encryption and quantum indistinguishability obfuscation.

In optical fibers, chips and other light-guiding devices, minor defects can scatter photons and disrupt their path. A new study demonstrates a way to reveal properties which, in certain systems, help light wave behavior withstand such flaws. The method could help speed up the search for new kinds of electronics and optical technologies, and contribute to more reliable quantum devices.

Researchers have developed and demonstrated a new hybrid photonic platform that integrates quantum emitters with photonic devices, providing a way to reliably control the interaction between photons and quantum information carriers. The chip-based platform, which combines gallium phosphide (GaP) with a diamond substrate, could help make quantum networks more practical by providing a way to connect quantum devices over long distances.

Some quantum systems are so complex that even the most powerful supercomputers struggle to simulate their behavior. One solution is quantum simulation: building a controllable quantum system in the lab and tuning it to mimic the one researchers want to understand.

Whether we are waiting for a car windshield to defrost in winter or a warm drink to cool down, how long it takes for an object to settle into a stable, even temperature within its environment (thermal equilibrium) depends on numerous factors. These can include surface area, the material properties of an object and airflow.

Laser amplification kicks off with just a few photons in the cavity, a regime where standard additive Langevin noise cannot capture the real fluctuations. To understand how this amplification begins, we map out a single-mode photon-carrier model that links macroscopic lasers directly into nanolasers. Stationary rate equations reveal that stimulated emission takes over across a tight pump window. In nanolasers, however, spontaneous processes coexist across a much broader range. Because steady-state averages miss the individual events that lead to the macroscopic photon number, we frame the stochastic dynamics around the actual discrete transitions, deriving a state-dependent diffusion approximation. The destruction of an excited carrier concurrent with the generation of a photon creates a negative photon-carrier cross-correlation. This unavoidably leads to a correlated, multiplicative Gaussian-noise framework. We track the resulting discrete dynamics with an established, event-based Laser Markov Chain (LMC) which stochastically samples pump, relaxation, emission, and cavity-loss events keeping all physical quantities as non-negative integers. Comparing its predictions to those of our multiplicative model proves that the latter reproduces excellently well the statistical behavior of photons and carrier, as long as a continuous diffusion description holds. Once the emission drops into the few-photon regime, however, the discrete model becomes indispensable. On the other hand, at large photon counts relative fluctuations shrink to a level where the state-dependence of the diffusion matrix can be ignored, to leading order, thus returning to the classic Langevin description of the system's stochastic dynamics.

Randomness certification aims to guarantee that the output of an untrusted quantum device contains genuine randomness that remains unpredictable even given quantum side information held by an adversary. For a classical verifier interacting with a single quantum device, such a guarantee cannot rely on the physical separation underlying standard Bell tests and must instead follow from computational restrictions on the prover. Building on the framework of Computational Bell Inequalities, we distinguish classical and quantum virtual-input hiding, showing that the former suffices for proofs of quantumness, whereas the latter enables randomness certification against quantum side information. Our main technical contribution is to establish quantum virtual-input hiding for a commitment-based protocol derived from the proof of quantumness from one-way-functions by Morimae and Yamakawa. We show that statistical hiding together with ordinary computational binding against quantum polynomial-time senders suffices, without requiring stronger quantum binding notions such as sum-binding or collapse-binding. This yields a randomness-certification protocol from post-quantum statistically hiding bit commitments. In particular, existing constructions of such commitments from post-quantum one-way permutations imply that post-quantum one-way permutations suffice for randomness certification. We further instantiate our construction using quantum-secure trapdoor claw-free functions, obtaining an efficient classical verifier, and in the quantum random oracle model, obtaining randomness certification without additional computational assumptions but with an inefficient verifier. These instantiations separate the cryptographic properties sufficient for randomness certification from the additional structure required for efficient verification within our commitment-based framework.

Wiring and bandwidth bottlenecks between a quantum processor and room-temperature electronics can be reduced by placing digital control at the cryogenic stage, but commercial foundry standard-cell libraries are not specified for operation at 4 K. A cryogenic recharacterization flow is therefore developed for a commercial 22 nm FD-SOI foundry standard-cell library using commercially available cryogenic compact-device models, while retaining the original cell circuits, layouts, logic functions, and implementation semantics and remaining compatible with the commercial synthesis, place-and-route, and signoff methodology used at room temperature. Body-bias dependence is quantified over 38,640 matched slew/load points at zero, +/-0.9 V, and +/-1.8 V body bias. Relative to full bias, zero-bias operation increases the median rising and falling delays by 38.6x and 33.0x, while approximately 90% of transitions exceed the foundry-defined maximum-transition envelope. The 0.8 V-to-0.4 V level shifter is even more sensitive to body bias: its worst-case falling delay decreases from 30.6 ns at zero bias to 0.56 ns at +/-1.8 V. For the outbound 0.4 V-to-0.8 V crossing, driving the 0.8 V receiver without a level shifter dissipates 57.7 uW of static power per bit at full bias, against 0.196 nW when level-shifted. In post-route analysis of the unchanged extracted physical database of a fabricated 32-bit ALU, the register-to-register setup boundary increases from 1.3 MHz at zero bias to 37.9 MHz at +/-0.9 V and 132.9 MHz at +/-1.8 V.

Two-band 2D fractional Chern insulators (FCIs) have recently been shown, in principle, to admit unusual anyonic order, associated with Bloch Hopfions localized in momentum space. Here we show that bounding the integrated quantum metric along one primitive Brillouin-zone cycle may refine this topological order to $|C|$ distinct braiding observables, cyclically permuted by lattice translations, for Chern numbers $|C| > 1$. The cyclic structure entails mildly non-abelian braiding phases and otherwise matches the spectral flow exhibited by the FCI's hybrid Wannier states, with the metric bound equivalently a bound on the states' real-space spread. We give a classification of quantum gates in principle implementable on this topological order; among them we find the non-Clifford T-gate and the non-Clifford entangling CCZ-gate. This points to novel pathways to fault-tolerant quantum processes within the known orbital structure of FCIs, potentially informing experimental searches towards hardware for future topological quantum computers.

We propose a scalable and efficient \textit{in situ} method for assessing the multiparticle indistinguishability of identical bosons or fermions in quantum interference experiments on linear interferometers by harnessing quantum parallelism and the bunching/anti-bunching tendencies of these particles. The proposed certification method can be applied to any generic linear interferometer. For particles occupying distinct input ports of a Haar-random unitary interferometer, the number of experimental runs required to attain a prescribed statistical precision is polynomial in the number of particles, the interferometer size, and the inverse precision, with high probability. Our method is robust under losses: for uniform particle losses, the polynomial scaling is preserved when the inverse single-particle survival probability is polynomially bounded. Our scheme is especially suitable for certifying the indistinguishability of single photons in large-scale interference experiments, such as Boson Sampling in the regime of quantum advantage over classical computation.

Bosonic particles beyond the Standard Model, such as axions, are among the leading candidates for dark matter. If such particles have a small mass, they are usually described as a purely classical field. However, it was recently shown that this description is incomplete: their inherent gravitational self-interactions can squeeze the field, producing a quantum feature beyond the classical description. Here we analyze squeezing of light dark matter in the presence of decoherence. We show that squeezing is continuously generated, and rapidly enough to survive dissipation, and may also remain present under thermal fluctuations and dephasing. Our results demonstrate that dark matter might possess persistent quantum features and motivate further investigation of their implications for dark matter detection.

With the escalating development of the quantum information technologies, the Rydberg atomic receiver has been envisioned as a promising alternative to its classical electronic counterparts, attracting extensive attentions from both physics and electronic engineering disciplines. By exploiting the electrical acuteness of Alkali atoms with diverse Rydberg energy states for electromagnetic field measurement, Rydberg atomic receiver is capable of surmounting the inherent limitations on the operating bandwidth and detection sensitivity of the classical electronic counterparts. Against this background, this article provides an extensive overview of Rydberg atomic communication and sensing from fundamental theory, critical technologies to practical implementations. Firstly, the milestones of the Rydberg atomic receiver evolution was introduced. Then we provide a clear understanding of Rydberg atomic receiver mechanisms from the perspective of classical communication and sensing, and highlight the unprecedented advantages over traditional electronic receivers as well as the technical challenges. Afterwards, necessary fundamentals are presented including the Rydberg atoms, typical non-coherent/coherent structures, and explicit experimental configurations, followed by discussions on state-of-the-art development of the Rydberg atomic receiver. Specifically, advancements on electric-field detection methods for accurate measurement of amplitude, phase, frequency and polarization, are extensively investigated. Based on the established methodologies, recent innovations in Rydberg atomic communication and sensing are reviewed, ranging from waveform design and array-based signal processing to radar applications like localization, imaging and remote sensing, with practical experimental results presented. Finally, we summarize the promising research trends around Rydberg atomic receiver.

We develop a quantum simulation framework for meson production in deep inelastic scattering based on light-front QCD Hamiltonian formalism. A quark-antiquark dipole, prepared either as a single-momentum state or as the $q\bar q$ component of a virtual photon, is evolved in real time through the color field of a nuclear target via Trotterized unitary evolution. We consider both proton and gold nuclear targets, each characterized by their respective saturation scale. From the evolved state we extract the transverse momentum broadening, the total and elastic cross sections, and the $J/ψ$ production rate by projecting onto the $J/ψ$ light-front wavefunction. We then extract the nuclear modification factor $R_A$ at different photon virtuality $Q^2$ and analyze nuclear modification effect. Results of classical simulations show good agreement with analytical eikonal predictions across a broad range of parameters. For the single-momentum dipole, quantum simulation is demonstrated on a quantum circuit emulator with a smaller lattice size, and results are consistent with the classical benchmark. This work establishes a first-principles, amplitude-level pathway toward computing exclusive hadron production in deep inelastic scattering, directly relevant to the physics program of the Electron-Ion Collider.

We show positive and negative results on classical relay channels with entanglement assistance, revealing a sharp contrast between strictly causal and causal relay encoding. First, we consider van der Meulen's setting of a unit-delay relay, with strictly causal encoding. We show that the standard cutset upper bound continues to hold with entanglement assistance, and deduce that entanglement does not increase the capacity for several classes of relay channels. Second, we consider a zero-delay relay, where the encoding is causal. We present an example in which entanglement enables rates that exceed the cutset upper bound by at least 12.5%. Namely, entanglement shared between the source and relay significantly increases the capacity of a classical zero-delay relay channel.

Under local magnetic Gauss constraints, vertex-disjoint regions can have commuting physical observable algebras that do not generate all observables on their union. We construct such counterexamples for every finite non-Abelian group on regular square tori, retaining the full magnetic physical space and original supports inside a fixed contractible disk. A peripheral projector selects inputs on which a joint transition preserves the constraints, while its loop factor alone fails the universal test over physical exterior completions. For a specified support family around a fixed eight-edge square loop, additivity fails if and only if the group is non-Abelian and each inner face is covered by at least one of its two prescribed peripheral edges. Leaving a face uncovered restores full additivity. For the same loop, additivity also holds with any region at vertex-set graph distance at least two. These results refute a recent group-double additivity proposition.

Hamming-weight computation and symmetric Boolean functions are basic primitives for quantum arithmetic and state preparation, where circuit depth and qubit overhead matter. We construct an exact circuit computing the Hamming weight of an $n$-qubit register with depth $O(\log n)$ and size $O(n\log n)$, using only the $n$ input qubits and $m=\lceil\log_2(n+1)\rceil$ binary output qubits. The circuit uses arbitrary one-qubit gates and CNOTs with all-to-all connectivity. Both depth and total width are optimal. Our constructions combine tree structures and pipelining, temporarily using input qubits as workspace. We also give exact circuits for every symmetric Boolean function with the same depth and size bounds, using only $m$ ancillary qubits returned to zero. Finally, we apply the counter to exact preparation of balanced Dicke states for even $n$. With only $O(\log n)$ ancillary qubits, we obtain expected depth $O(\log^2 n)$ using measurements and classical feedforward, and depth $O(n^{1/4}\log n)$ using unitary gates alone.

We identify a strong quantum Mpemba effect in which a many-body ground state heats faster than every Gibbs state at finite positive temperature under the same dissipative dynamics within a fixed-color sector. In ferromagnetic $SU(N)$ exchange systems with local dephasing, exact coherence shells confine the ground-state evolution and exclude all slower Liouvillian modes. Its relaxation rate is fixed by the bath, independently of system size, exchange graph, and integrability. We derive an energy-resolved sign criterion that guarantees a slower thermal contribution throughout the positive-temperature range. An exact finite-chain solution proves this rate inversion, and symmetry-resolved calculations confirm the criterion in larger spin-one chains, including nonintegrable exchange. The zero-temperature endpoint of a continuous Gibbs family can therefore be dynamically isolated by its exact exclusion from slow relaxation channels.

We present a continuity bound for quantum conditional entropies in terms of fidelity, with no dependence on the dimension of the conditioning system. Our results encompass both the von Neumann entropy and one version of sandwiched Rényi entropy, which is particularly relevant for applications in quantum key distribution (QKD). In such applications, this bound should provide improved results as compared to previous continuity bounds based on trace distance. We also show that the bounds can be sharpened as expected for classical-quantum states, and verify that they hold when the conditioning system has countably infinite dimension. Finally, we present several variants tailored for exponential functions of the Rényi entropies instead, which should be relevant for QKD applications.

Consider $N$ identical quantum systems at the vertices of a graph, interacting via pairwise edge couplings. We designate $K$ vertices as a system of interest $\mathrm S$ and the remaining $N-K$ as a reservoir $\mathrm R$. Under generic connectivity assumptions between $\mathrm S$ and $\mathrm R$, we show that for $N\to\infty$, the reduced state of $\mathrm S$ converges to a convex combination of symmetric product states of $K$ single-vertex density matrices -- called a de Finetti representation. Unlike in standard derivations for symmetric (exchangeable) systems, we establish de Finetti representations for quantum networks, which are inherently non-exchangeable. We construct the representations explicitly and quantify the convergence rate. We show that Erdős--Rényi random graphs exhibit the de Finetti structure: as the reservoir grows, the reduced state of any fixed finite subgraph converges almost surely to an explicit deterministic product state. As applications, we establish a general area law for the entanglement entropy of $\mathrm S$, analyze mean-field and fluctuation scalings of the $\mathrm S$-$\mathrm R$ interaction, and illustrate our results on qubit networks. We also derive quantitative convergence estimates for information-theoretic quantities, including von Neumann entropy, mutual information, and entanglement within $\mathrm S$ and between $\mathrm S$ and $\mathrm R$.

We prove that the random phase approximation provides an upper bound on the correlation energy of a three-dimensional, weakly interacting, Fermi gas in the thermodynamic limit at high density. More precisely, we consider a mean-field scaling regime where the kinetic and interaction Hamiltonian are scaled by $ρ^{-2/3}$ and $ρ^{-1}$, respectively. We use a correlated trial state constructed through a quasi-bosonic Bogoliubov transformation of collective particle--hole excitations associated to patches on the Fermi surface. Key of the proof is to control the position-space localization of the collective excitations. Combined with an iterated Duhamel expansion of the expectation values of (localized) particle number operators we obtain extensive estimates, which justify the reduction to an effective quadratic Hamiltonian and its approximate diagonalization.

Nonrelativistic quantum chemistry is based on the Schrödinger equation in continuous, unbounded space. Computational approaches on classical and quantum computers often truncate the spatial domain and introduce a finite-dimensional basis, reducing the continuum problem to a finite-dimensional one. There is therefore a fundamental question: to what extent does this approximation capture the original continuum problem? In this work, we develop a general Sobolev-Galerkin framework for estimating spatial discretization errors in quantum simulation with unbounded Hamiltonians. We apply this framework to many-body Coulomb systems and establish both periodization and Galerkin error estimates for wave-function dynamics and ground-state energies. For dynamics, the finite-basis projection error of the exact wave function does not capture the full basis-discretization error: an additional dynamical projection error enters our bound at a different rate, and we introduce an inner-product argument to control this contribution. Interestingly, the spatial convergence rates for wave-function dynamics and ground-state energies differ quantitatively. For ground-state energies, we establish a sharp $M^{-1}$ convergence rate at fixed cell size, where $M$ is the number of one-particle basis functions. We also show that a uniform $M^{-1}$ convergence rate is impossible for the corresponding real-time wave-function error with general $H^2$ initial data. The analysis relies on many-body Sobolev estimates with explicit polynomial dependence on system size. Combining these estimates with state-of-the-art quantum algorithms, we obtain, to our knowledge, the first rigorous end-to-end complexity bounds for quantum simulation of molecular and electronic dynamics with all spatial errors explicitly controlled. The number of basis functions is determined directly from the continuum problem, without regularization.

Recent work by Greenblatt, Lange, Marcelli, and Porta (Commun. Math. Phys. 2024) provides the first rigorous justification of adiabatic theory for interacting quantum systems at positive temperature. Their analysis treats weakly interacting lattice fermions and combines a rigorous Wick rotation with fermionic cluster expansion techniques. Here, we study a class of weakly interacting quantum spin systems and derive response theory at positive temperature, thereby covering non-Fermi systems for the first time. Our proof identifies and exploits the locality property of local indistinguishability as a key ingredient in carrying out low-temperature adiabatic expansions. The fact that these systems satisfy local indistinguishability was recently established jointly with Adhikari (arXiv:2508.15907) using cluster expansion methods together with a probabilistic swapping trick.

Noisy Intermediate-Scale Quantum (NISQ) hardware has transformed quantum computing into a practical experimental platform while introducing fundamental challenges associated with hardware noise, decoherence, and probabilistic execution. Although quantum software testing (QST) has rapidly emerged as an active research area, it remains unclear to what extent existing testing methodologies explicitly engage with noisy and hardware-constrained execution environments. This paper presents a systematic empirical landscape analysis of noise-awareness in QST research through a deterministic, taxonomy-guided analytical framework applied to 61 papers published between 2018 and 2025 across eight testing paradigms, contrasting how contributions are framed with how they are evaluated. Among the analyzed papers, 47 (77.0%) are noise-oblivious and only 14 (23.0%) explicitly engage with noise-related execution concerns, while only 11 (18.0%) report evaluation on physical hardware or a noisy simulator. Test generation, the largest paradigm, exhibits a noise-awareness rate of only 14.3%, and debugging and repair 18.2%; coverage-based, metamorphic, and differential testing contain no noise-aware contributions. Noise-aware methodologies emerged late and remain outnumbered in all analyzed years. Framing and evaluation are strongly associated (odds ratio 40.5, p < 0.001) yet diverge for individual papers: 5 of the 14 noise-aware papers evaluate only on ideal simulators. Inferential statistical tests are reported in only 16.4% of papers. The classification framework was validated against a blinded, human-coded reference sample, achieving almost perfect inter-rater agreement on testing-technique classification and substantial agreement on noise-awareness. The framework provides a reusable empirical basis for longitudinal analysis of hardware-conscious testing practice.

The realization of fault-tolerant quantum computation relies on Quantum Error-Correcting Codes (QECC). Of particular interest are codes that combine a high encoding rate with sufficient distance. Existing algebraic constructions, such as lifted product (LP) codes, build a large quantum low-density parity-check (qLDPC) code from a classical base matrix. In this work we introduce LiftDiff, a generative approach to the discovery of QECC. A discrete denoising diffusion model is trained to generate base matrices over the group algebra $\mathbb{F}_2[\mathbb{Z}_\ell]$, which are then expanded into LP codes. The reverse diffusion process is guided by an energy function that evaluates quantum code properties, including girth, degree, sparsity and decoding performance, steering the sampler toward matrices that yield LP codes with favorable parameters. Our method discovers codes with parameters such as $[[169,13,11]]$, $[[143,15,9]]$, and $[[260,24,10]]$, including a $[[247,19,14]]$ code that achieves the highest ${kd^2}/{n}$ among the baselines. Moreover, several discovered codes outperform the Gross code across a broad range of the tested physical error rates under both code-capacity and circuit-level noise.

Quantum Key Distribution (QKD) supports secure key establishment under ideal protocol assumptions, but practical systems remain exposed to implementation-level attacks against optical channels, detectors, and controller behavior. This study presents Quantum Forensic Log (QF-LOG), a simulation-based forensic framework for analyzing aggregated QKD operational logs rather than raw quantum states. QF-LOG uses four observable features: quantum bit error rate (QBER), photon count, latency in milliseconds, and abort flag. The framework classifies normal operation and three simulated attack-related conditions: partial intercept-resend, detector-blind, and fiber-tap. A physics-inspired Generator-A dataset with 5 million balanced records was constructed using explicit mathematical generation models for all four features. A transparent threshold baseline, logistic regression, random forest, and XGBoost were evaluated on Generator-A. The full-feature learning models achieved macro F1-scores from 0.8211 to 0.8243 and outperformed the transparent two-feature comparator. Feature diagnostics showed that QBER contributed most, followed by latency in milliseconds and photon count, while no single feature reproduced the full feature set performance. Robustness was assessed on a separately generated Generator-B dataset of 5 million records that uses the same governing equations under shifted simulated operating parameters. Without retraining or tuning, their macro F1-scores decreased to values from 0.5645 to 0.5669. These findings show that QF-LOG can support interpretable forensic classification in a controlled synthetic setting, but stable internal evaluation does not establish reliability under changed simulated QKD operating conditions. The framework provides a documented basis for future evaluation across broader simulated settings and hardware-generated QKD logs.

Inner products of random matrices and random quantum states---such as orbital inner products, expectation values, overlaps, and cyclic Bargmann invariants---are shown to follow from two underlying mechanisms: the diagonal of an induced random state is Dirichlet distributed, and the expectation value of a random pure state in a rank-one or two-by-two operator is a numerical shadow on an elliptical disk. For states induced by an environment of dimension $K$, the expectation value of any observable is a Curry--Schoenberg spline with each eigenvalue repeated $K$ times, and the vector of moments has an explicit density on a simplex; for a qutrit, the variance law is obtained in finite form. The overlap of two random qubit states attains its mode at its mean for every rotation-invariant ensemble, but for Hilbert--Schmidt qutrits the density at the mean has a strictly negative derivative, so mode and mean separate; for large environments, the centred overlap converges to a variance-gamma law rather than a Gaussian. For two noncommuting qubit observables, the joint law of the two standard deviations is derived for all $K$, and the probability of coming within a small distance of the optimal sum of variances scales as a power of that distance, with a different exponent when the Bloch axes are orthogonal. For three Haar-random qubit states, the exact density of the Bargmann invariant is given in terms of a complete elliptic integral, together with its local behaviour and elementary marginals. In every dimension, the probability that its real part is negative---certifying basis-independent coherence---is computed, along with all mixed moments. For cycles of arbitrary length, the invariant is shown to be driven by an exact three-parameter Markov chain, and the logarithm of its modulus obeys a law of large numbers and a central limit theorem.

We obtain an exact closed-form total photon count for a prescribed Newtonian Kepler parabola, with a fully relativistic treatment of its radiation. We also obtain closed expressions for the angularly resolved photon spectrum and elementary expressions for the total radiated energy and momenta. The count is finite, scale-independent, and analytic in subluminal speed at closest approach. At large maximum rapidity $η$, $N\sim(7α/\sqrt6)η$, while $E\propto e^{3η}$ at fixed passage timescale: the radiation chiefly hardens. For slow motion at fixed coupling and closest distance, a nearby ellipse emits fewer photons but more energy and angular momentum per orbit. The hyperbolic photon count remains IR divergent arbitrarily close to threshold, while the count at the exact parabolic threshold is finite.

We investigate how structural correlations beyond the power spectrum affect phonon counting in a one-dimensional acoustic stack. An integer-thickness construction cancels the extensive leading backscattering term and leaves a finite-chain reflection amplitude determined by endpoint innovations. For symmetric independent innovations with unit variance and fourth moment $μ_4$, the normalized reflected-power second moment tends to $(μ_4+5)/4$. With vacuum environmental inputs, a two-phonon Fock input therefore gives an ensemble-averaged reflected factorial correlation $g^{(2)}=(μ_4+5)/8$. Two explicitly constructed ensembles with identical mean and complete two-point correlation function yield $g^{(2)}=3/4$ and $9/8$, placing their counting variances on opposite sides of the Poisson value. Conditional tensor averaging also gives a general fourth-order resistance-growth coefficient for arbitrary impedance contrast, including a positive higher-scattering contribution not recovered by shifting the lowest-order spectrum. Exact enumeration confirms the fixed-$N$, small-detuning limit and shows that increasing $N$ at fixed detuning produces a crossover governed by accumulated higher-order bulk scattering rather than convergence to the endpoint formula. Further calculations test bandwidth, thickness error, propagation loss and thermal background. The result concerns disorder-averaged pulse statistics; it neither creates nonclassicality from coherent input nor changes the conditional factorial correlation of an individually resolved passive sample.

Reliable quantum computation requires methods for verifying quantum circuits. Level-synchronized tree automata (LSTAs) were recently introduced to represent sets of quantum states for this purpose. We study LSTAs along two axes relevant to verification: the complexity of their decision problems and the size of their representations under circuit operations. We prove that acyclic LSTAs have NP-complete nonemptiness and $Π_2^P$-complete language inclusion, and that general language inclusion is EXPSPACE-complete. We further prove inherent quadratic representation growth under individual quantum gates in a fixed qubit order, and give an adjacent-qubit reordering construction that preserves level synchronization. These results clarify the scope of applicability of the automata-theoretic toolbox for quantum circuit verification.

We characterize the hybrid Fourier transform on the Schwartz--Grassmann space $\caS(\bbR^m)\otimesΛ_{2n}$ by operator intertwining relations. Using the bosonic oscillator Howe decomposition and the fermionic Lefschetz decomposition, we describe the action of the hybrid Fourier transform on both tensor factors. We show that first-order covariance with respect to coordinate multiplication and differentiation determines the transform up to a scalar. For $m,n\ge1$, we prove that covariance under all even quadratic operators, together with any one nonzero mixed quadratic operator, determines the linear span of the hybrid Fourier transform and its inverse. This rigidity result is obtained by computing the ordinary commutants of the even and full quadratic oscillator actions of $\fosp(4n|2m)$. After a degree-scaling change of normalization, we make the hybrid Fourier transform unitary with respect to the occupation number inner product, and factor it into a bosonic oscillator rotation and (up to a scalar phase) an $SU(2)$ rotation in the fermionic Lefschetz representation. For $m=1$ and $n\ge2$, we show that full even quadratic covariance together with the parity-preserving cubic relation for $qQ_f$ determines the unitary transform up to a global phase and a fermion-parity phase. Finally we calculate the unitary conjugation formulas for Hubbard--Holstein Hamiltonian for a hybrid continuous-variable and discrete-variable quantum system.

Two-dimensional quadratic band crossing point (QBCP) semimetals serve as a fertile platform for interaction-driven quantum criticality, nevertheless, the role of the complete fermion-fermion interactions remains largely unexplored. To address this, we systematically investigate the low-energy physics of a spin-1/2 checkerboard-lattice QBCP semimetal by considering all 16 marginally short-range fermion-fermion interactions. Using the momentum-shell renormalization group, we derive the coupled flow equations, which reveal that the low-energy physics is governed by a series of fixed points. Depending on the initial conditions, the system may exhibit a single stable fixed point, several discrete fixed points, or three continuous groups of fixed points parameterized by a few variables. By introducing source terms and evaluating susceptibilities, we identify the dominant and subdominant instabilities. The leading phases include nematic spin-nematic (NSN), quantum anomalous Hall (QAH), chiral superconducting ($\mathrm{SC}_1$), and quantum spin Hall (QSH) orders. Moreover, several features distinguish our findings from previous simplified models. Off-diagonal interactions generate terms that promote orders absent in such models, the continuous groups allow systematic tuning of the leading instability, and trajectory-dependent instabilities emerge where the full RG flow, rather than the fixed point alone, determines the dominant state. These results offer a comprehensive theoretical understanding of low-energy quantum critical behaviors and phase instabilities in two-dimensional QBCP semimetals and related electron systems.

Reconfigurable neutral-atom processors require rapid, high-fidelity transport of atoms between optical-tweezer sites. In finite-depth Gaussian traps, fast motion can leave residual motional excitation even when the atom reaches its destination. We develop a basis-parameterized gradient-ascent pulse-engineering (GRAPE) framework for one-dimensional transport of a single $^{87}$Rb atom. A shortcut-to-adiabaticity reference is refined using 17 trajectory parameters, with ten additional parameters providing bounded trap-depth modulation; depth affects both confinement and the inverse construction of the physical trap center. For a $12.6\,μ$m transfer completed in only $30.5\,μ$s, corresponding to approximately $2.75$ periods of the reference trap, the selected joint protocol achieves a ground-state infidelity of $2.41\times10^{-7}$. Because preparing an exactly pure motional ground state is experimentally challenging, we also optimize population-weighted transport for initial distributions with mean vibrational occupations $\nbar\simeq0.16$ and $1.87$, reaching same-state probabilities of about $0.99993$ and $0.9934$. Trap-depth fluctuations can further degrade transport fidelity. Robust optimization under a measurement-informed depth-noise model improves the mean error, worst sampled error, and fidelity dispersion for the specified noise realizations. Coordinated control of tweezer position and confinement thus offers a route to rapid transport with low residual excitation for flexible atom rearrangement and dynamic connectivity in neutral-atom processors.

Controlling quantum hardware requires choosing and revising experimental strategies as nonlinear response, coupling, and drift limit calibration. We experimentally investigate a general-purpose large language model (LLM) as a human-in-the-loop strategy layer for a neutral-atom tweezer platform. Through step-by-step interaction with experimental feedback, the LLM guides a transition from multiplicative row--column correction to a drift-corrected local response-matrix method when separable feedback stalls. Deterministic software performs image analysis and numerical updates, while an experimentalist verifies and authorizes each waveform. For a $10\times10$ crossed-acousto-optic-deflector array, this workflow reduces the Gaussian-peak coefficient of variation from $20.30\%$ to $1.57\%$ in 30 candidate-update rounds. The experiment demonstrates feedback-informed strategy selection on a physical quantum-control subsystem, rather than direct generation of control parameters alone. These results highlight the potential of LLMs to guide control optimization across diverse quantum platforms by adaptively formulating and refining experimental strategies.

Bound states in the continuum (BICs) remain localized despite the presence of extended modes at the same energy. In driven systems with long-range couplings, the absence of radiation does not by itself determine how a bound state decays in space. We study a Hermitian Rydberg spin waveguide coupled to a four-site plaquette, where a winding drive phase combines rotation with time translation to forbid propagating guide channels in one symmetry sector. The resulting eigenstate remains embedded in the continuum of other sectors and carries an inverse-cube waveguide amplitude, with coherent contributions from direct plaquette--guide coupling and long-range guide propagation. Pair-state calculations determine the microscopic couplings in the axial geometry, while coherent Floquet mixing sets the weight of the dominant circulating plaquette mode. The bound state thus retains the spatial signature of the long-range coupling even when radiation is forbidden.

Optical initialization and readout of molecular electron spins in water remains challenging for 3d transition-metal complexes. Their Laporte-forbidden d-d transitions yield weak transition dipole moments, so optical spin detection in aqueous Cu(II) previously required ~1 M concentrations. Here we overcome this constraint through symmetry-breaking chelation. Coordinating Cu(II) with EDTA imposes a non-centrosymmetric ligand field with enhanced metal-ligand covalency, relaxing Laporte restrictions and amplifying d-d transition dipole moments. This design enhances absorption and magnetic circular dichroism by 7.3- and 5.6-fold, enabling ultrafast spin readout down to 100 μM with an apparent dephasing time T2^*~0.54 ns. As a proof-of-concept for selective molecular-spin sensing, histidine addition extends T_2^* to ~0.8 ns in a concentration-dependent manner, whereas glycine produces no measurable effect. These results show that symmetry breaking provides a strategy to create molecular spin-photon interfaces, opening avenues toward all-optical, analyte-responsive quantum sensing in water.

Researchers at RIKEN and collaborators have achieved high-fidelity simultaneous control of five silicon spin qubits, maintaining over 99.9% accuracy. They overcame crosstalk caused by AC-Stark shifts through a new calibration protocol, enabling the use of a single microwave control line. This breakthrough meets the fault-tolerant threshold for quantum error correction and paves the way for more scalable quantum computers. The post RIKEN Demonstrates High-Fidelity Simultaneous Control of Silicon Spin Qubits Above 99.9% Threshold appeared first on Quantum Computing Report .

A joint study by Chalmers Next Labs AB, ConScience AB, and Singapore’s National Quantum Federated Foundry (NQFF) validated the stability of a superconducting quantum processor (QiB1) when transported between international research facilities. The study, conducted under the WACQT–NQFF Twin Testbed initiative, confirmed that environmental changes between Gothenburg and Singapore did not degrade the processor’s performance. This collaboration is now being commercialized as a standardized cross-facility measurement service. The post Chalmers Next Labs, ConScience, and NQFF Validate Superconducting Qubit Chip Stability Across International Testbeds appeared first on Quantum Computing Report .

Kipu Quantum demonstrated a novel method for molecular toxicity classification using analog quantum feature extraction on QuEra's 256-qubit Aquila neutral-atom quantum processor. This approach, detailed in their technical report, utilizes 200-qubit neutral-atom arrays to generate high-dimensional quantum features. These quantum features significantly improved performance over classical methods, particularly on imbalanced datasets, doubling the F1-score and raising balanced accuracy for drug discovery and chemical safety. The post Kipu Quantum Demonstrates Neutral-Atom Quantum Feature Extraction for Molecular Toxicity Classification on QuEra Hardware appeared first on Quantum Computing Report .

MIT researchers used a specialized self-attention neural network to solve complex equations related to quantum particles, confirming the existence of anti-Pfaffian topological states. This breakthrough provides a roadmap for building noise-resistant topological qubits in materials like monolayer WSe2 and semiconductor quantum wells. The post MIT Physicists Use First-Principles AI to Resolve Non-Abelian Anyon Order at Strong Landau Level Mixing appeared first on Quantum Computing Report .

Guest Post By George Varghese, Head of Investment, 0G Labs We&#8217;re witnessing one of the largest infrastructure investment cycles in modern technology, and I believe we&#8217;re still early in understanding its economic potential. AI has already changed how companies think about computing, with enormous investment flowing into GPUs, data centres, energy infrastructure and models. As AI expands across industries, computational demand has room to grow. Quantum computing could add another dimension to that growth. Hardware and error-correction progress is accelerating research, and I see enormous potential in combining quantum capabilities with today&#8217;s AI systems. The opportunity extends across hardware, software and connecting infrastructure. The investment case for AI infrastructure remains strong. Enterprises are incorporating AI into core processes, while reasoning models, multimodal systems and autonomous agents are widening the range of applications worth deploying. Each advance brings new requirements for computing, networking, storage and power. More efficient models can lower the cost of individual tasks, making additional applications commercially viable and potentially expanding overall demand. I expect sustained investment across computing. Still, investors need to understand the economics of individual assets. A data centre can operate for decades while the chips inside it undergo several replacement cycles. Changes in hardware performance, software efficiency and utilisation affect returns, even when aggregate demand continues growing. That is why I pay close attention to infrastructure that can accommodate changing computational requirements without excessive reinvestment.&nbsp; I&#8217;m particularly optimistic about quantum computing&#8217;s potential in fields where computational complexity currently limits progress. Molecular simulation, materials science and certain optimization problems are promising areas, although the practical advantag

Yuval interviews Robert Wille, a computer scientist and co-founder focused on quantum computing software. They discuss the field’s transition from research to practical deployment, the need for heterogeneous and hardware-agnostic software stacks, and the integration of quantum into HPC environments. Robert explains the importance of design automation, open-source strategy, and AI-assisted development, arguing that quantum’s complex optimization challenges resemble those long solved in classical computing. Transcript Yuval: &nbsp;Hello Robert and thank you for joining me today. Robert: &nbsp;Hello Yuval, happy to be here. Yuval: &nbsp;So who are you and what do you do? Robert: &nbsp;Yeah, I&#8217;m Robert, I&#8217;m a computer scientist by training and for more than 15 years now actually involved in quantum computing. We are building software for quantum computing, which is important because it is awesome to have great quantum computing hardware and have great quantum computing applications, but you definitely need software to connect the end users to the hardware and to make these applications work. Yuval: &nbsp;I think you have at least two hats, right? One is an academic and the other is an entrepreneur. Could you tell us a little bit about that, please? Robert: &nbsp;Absolutely. By heart, I&#8217;m an academic and a researcher. I work at the Technical University of Munich and at the same time we also figured out it is great to do innovation at the university, in an academic setting, but for real impact we also need production-ready software and this cannot really be done at the university environment anymore. That&#8217;s why a little bit more than a year ago we also founded a company, and there we now take all the innovation from the academic developments and make it production-ready in a commercial context. Yuval: &nbsp;Since you&#8217;ve been doing it for so long, software in the context of quantum, where are we today? What is the state of quantum software tod

Open Quantum has launched a native Qrisp integration, enabling high-level QPU execution across IonQ, Rigetti, IQM, and AQT hardware. This allows developers to compile and execute Qrisp programs directly on physical QPUs without writing vendor-specific gate-level code. The integration simplifies quantum programming by providing software-engineering abstractions, automated qubit allocation, and memory management. The post Open Quantum Launches Native Qrisp Integration for High-Level QPU Execution Across IonQ, Rigetti, IQM, and AQT Hardware appeared first on Quantum Computing Report .

Researchers from Harvard, Anthropic, and QuEra Computing developed an AI framework that uses Large Language Models (LLMs) to discover and optimize fault-tolerant quantum circuits. This framework significantly reduces the resource costs of core computational primitives, achieving up to 9,100x lower costs compared to hand-crafted baselines. The LLMs achieved this by proposing complete Python programs for circuits, which were then evaluated and refined through an evolutionary process, leading to the discovery of new co-design principles and circuit architectures. The post Harvard, Anthropic, and QuEra Use LLMs to Discover Quantum Circuits with Up to 9,100x Lower Resource Costs appeared first on Quantum Computing Report .

D-Wave has successfully demonstrated 3D analog-digital quantum simulation of higher-order topological insulators using up to 728 qubits on an Advantage2 superconducting quantum annealing processor. This achievement, detailed in a research study on arXiv, involved new analog-digital quantum control protocols to measure localized boundary modes and extract 3D bulk topological invariants. This breakthrough confirms the utility of analog-digital quantum annealing hardware as a programmable simulator for condensed matter physics and topological materials. The post D-Wave Demonstrates 3D Analog-Digital Quantum Simulation of Higher-Order Topological Insulators Using 728 Qubits appeared first on Quantum Computing Report .

Johannes Pollanen, co-founder of EeroQ and a professor of physics at Michigan State University, explains how EeroQ builds qubits from single electrons floating on a film of superfluid helium, and why he thinks the semiconductor chip is the only proven way to scale a quantum computer. The post Podcast with Johannes Pollanen, Co-founder of EeroQ and a Professor of Physics at Michigan State University appeared first on Quantum Computing Report .

Manipal Institute of Technology (MIT Bengaluru) has inaugurated the Manipal House of Quantum (Q-HUB@MAHE) in Bengaluru, India, on October 13, 2026. This facility features QuantrolOx’s VIDYAQAR open-architecture quantum system, a 25-qubit-capable dilution refrigeration platform that is part of a national roadmap to scale to over 1,000 qubits. The initiative aims to train 100 quantum engineers by December 2026 and allows researchers to test and benchmark quantum components using custom Python workflows. The post MIT Bengaluru Inaugurates Q-HUB@MAHE and Deploys QuantrolOx&#8217;s Open-Architecture VIDYAQAR Quantum System appeared first on Quantum Computing Report .

Qubits, the quantum equivalent of digital bits, are fragile and prone to errors. That makes building reliable quantum computers extremely difficult. One fix has been to use traditional magic state distillation, which filters out flaws, but it is extremely resource-intensive.

Insider Brief Anthropic and Harvard researchers used Claude to design more efficient quantum circuits across eight tasks, reducing estimated computing resources for key routines used in quantum algorithms. One redesigned decoding circuit used roughly 12 times fewer costly quantum operations, while a new arithmetic design offered improved trade-offs between gate counts and qubit requirements. The results were evaluated through computational checks and resource estimates rather than demonstrations on quantum hardware, and practical benefits will depend on integration into complete algorithms and machines. A team of researchers from Anthropic and Harvard used an artificial intelligence (AI) system to design quantum circuits that require fewer operations and qubits, potentially lowering the hardware demands of useful quantum computing. The researchers, who posted their work on the preprint server arXiv, tested the approach on eight computational building blocks used in chemistry, optimization, physics simulation and number theory. Seven of those designs reduced both the number of costly quantum operations and the number of qubits compared with the study’s baselines. The eighth produced a new approach to arithmetic that offers better choices between computing time and memory. The results concern circuit designs and resource estimates, rather than calculations demonstrated on a working quantum computer. The team nevertheless addressed a central problem for the industry that, in order for quantum computers to become more useful quantum, algorithms will need to improve computing alongside the development larger, more reliable machines. According to the study, one redesigned decoding circuit required about 440,000 Toffoli gates, down from 5.1 million in the comparison design, while reducing its peak qubit requirement from 1,938 to 1,837. Toffoli gates are operations that are particularly costly in many proposed error-corrected quantum computers, making their number a useful

A new review paper by Hoong Chuin Lau examines the intersection of AI and quantum computing for combinatorial optimization, categorizing research into three paradigms: AI-for-Quantum Optimization (AI-for-QO), Quantum-for-AI (Q-for-AI), and AI-Quantum Co-Optimization. The study, which analyzed 119 papers, concludes that AI-assisted quantum optimization shows promise, while quantum-assisted AI models are largely unproven. The review emphasizes that scaling quantum optimization is a systems engineering problem requiring selective quantum use, with only a few studies isolating quantum contributions or establishing classical baselines. The post Review Evaluates AI and Quantum Computing Paradigms for Adaptive Combinatorial Optimization appeared first on Quantum Computing Report .

The European Quantum Industry Consortium (QuIC) has published a position paper urging the European Commission to harmonize EU dual-use controls on quantum technologies. They warn that fragmented national implementations of export controls on quantum technologies are causing administrative difficulties, shipment delays, and revenue loss for European quantum companies. QuIC proposes reforms focusing on single market harmonization, expanded allied trade, clearer rules for intangible transfers and cloud access, and differentiated scrutiny for supply chain components to ensure European competitiveness. The post QuIC Publishes Position Paper Calling for Harmonized EU Dual-Use Controls on Quantum Technologies appeared first on Quantum Computing Report .

Physicists at the University of Oxford have developed a quantum network using different atomic elements, strontium and calcium, to create entangled states. They successfully generated up to 4-qubit Greenberger-Horne-Zeilinger (GHZ) states and stored this entanglement in calcium memory qubits for over 10 seconds. This significantly extends entanglement lifetimes, marking a major step forward for distributed quantum computing and sensing. The post University of Oxford Entangles Multi-Species Atom Network and Extends Memory Storage Beyond 10 Seconds appeared first on Quantum Computing Report .

Kipu Quantum and NTT DATA have partnered to advance enterprise quantum computing and QML solutions. The collaboration will integrate quantum algorithms into existing enterprise technology, leveraging Kipu Quantum's expertise in hardware-specific compression techniques. This partnership, which began with a pilot program at Komatsu Peru, aims to develop and deploy commercial algorithms for various applications, including supply chain logistics and financial risk modeling, initially in Latin America and then globally. The post Kipu Quantum and NTT DATA Partner to Scale Enterprise Quantum Computing and QML Applications appeared first on Quantum Computing Report .

We argue that the experimental measurement of the lifetime and decay law of metastable helium is a promising way to find a deviation from quantum mechanics. We analyze the decay of the metastable state for a quartic deformation of quantum mechanics. We find that the absolute change of the mean lifetime can be significant even if the modification is small. We show that, in the Wigner--Weisskopf approximation, the deviation from the exponential law in the modified theory can occur on time scales comparable with the lifetime.

We analytically characterize how the location and the local or correlated structure of stochastic Pauli errors affect a three-qubit coherent quantum-teleportation circuit. Independent local channels and a fully correlated two-qubit channel are inserted separately in six configurations. Propagating each Pauli-error realization through the Clifford circuit yields the effective channel on Bob's qubit and analytical expressions for the average and state-resolved fidelities. Under a common ordered-pair probability convention, the six configurations form three pairs that induce equivalent reduced channels on Bob. Within each pair, corresponding Pauli-error realizations have the same probabilities and produce the same effective Pauli operator on Bob's output state. The equivalence therefore holds for every input state within the stochastic Pauli models considered here, rather than only for the average fidelity. Correlated Z errors do not affect the output for the first pair; local X and Z errors exhibit complementary qubit sensitivity for the second; and correlated same-axis Pauli errors cancel for the third. These results classify the error response of the selected circuit configurations and show that it depends jointly on the error statistics, Pauli axis, and position within the protocol.

Nitrogen vacancy centers in diamond (NVs) are point defects well suited to quantum sensing of magnetic fields. NV spin states can be initialized and read out optically with high spatial resolution, enabling detection of pL-scale volumes of nuclear spins. Using Coherently Averaged Synchronized Readout (CASR), standard NMR spectroscopy techniques such as free decay, spin echo, and PGSE have been performed with Hz-scale spectral resolution using NV-diamond sensors. However, using NV detection for conventional high-resolution NMR at multi-tesla fields is challenging due to the need to manipulate NV electronic spins at resonance frequencies 100 GHz or higher. Low-field J-coupling spectroscopy provides an alternative path to chemical resolution in a regime more easily accessible to NVs. Here, we demonstrate homonuclear and heteronuclear J-coupling spectroscopy using an NV-NMR spectrometer based on permanent magnets operating at $\sim$890 kHz proton Larmor frequency (bias magnetic field $\sim$21 mT). This field strength enables chemical characterization based on J-coupling using sequences such as Synchronized Echo (SyncE) and Spin-Echo Double Resonance (SEDOR), which do not require the strong chemical shift dispersion and pristine field homogeneity of high-field NMR. The frequency range is easily detected by NVs using standard XY dynamical decoupling sequences and is well-suited for applying Overhauser DNP, which can boost proton signal by two orders of magnitude. We acquire initial NV-NMR measurements of T$_1$, T$_2$, and Overhauser DNP in glycerol before advancing to SEDOR spectroscopy of methanol-$^{13}$C and a methanol-$^{13}$C/acetonitrile-2-$^{13}$C mixture at sample volumes $\sim$50 pL, in which we demonstrate measurement of $^1J_\text{CH}$ couplings and resolution between species. We also acquire a homonuclear J-coupling spectrum of a natural-abundance propylene carbonate sample.

Semiconductor quantum dots (QDs) are essential components for integrated photonic and quantum information systems, yet current epitaxial growth techniques face significant limitations in complexity of growth, material selection, and density tunability. Here we report a displacement etch technique that enables controlled formation of GaAsSb QDs with emission at telecommunications wavelengths. Our approach uses arsenic molecular flux (As$_2$) to react with antimonide surfaces through thermodynamically favorable displacement reactions, creating three-dimensional quantum confined nanostructures without requiring strain-driven growth or complex droplet-based processes. Density functional theory shows the two competing As-for-Sb exchange pathways to be nearly equivalent in both reaction energy and activation barrier, which places morphological control in the subsequent adatom kinetics rather than in the surface reaction itself. A single process parameter, the As$_2$ exposure, sets the QD areal density across three orders of magnitude, from 10$^2$ to 10$^5$ $μm^{-2}$, covering both isolated emitters and dense gain media. Structural analysis reveals well-defined GaAsSb QDs with a mixed GaAs/GaSb composition and no extended defects. Temperature-dependent photoluminescence measurements confirm emission at 1550 nm (0.8 eV) within the telecommunications C-band, with characteristic QD-like temperature dependence. Because the QDs form on a lattice-matched GaSb surface in a single growth step, the technique offers a practical route to C-band emitters built into the GaSb/AlGaSb device family already used for mid-infrared sources and detectors.

We study an adiabatic controlled-$Z$ (CZ) gate for neutral atoms in which dipole-dipole coupling between nearly degenerate Rydberg pair states enhances the interaction between dressed ground states. This coupling produces an avoided crossing in the two-atom dressed-state spectrum. Approaching the crossing enhances the dressed interaction, but also reduces the dressed-state gap and increases the Rydberg admixture. We identify a Förster-enhanced operating range in which the required conditional phase is accumulated with adiabatic return and small transient Rydberg population. We then analyze the finite-time dynamics of the two-qubit computational states under a smooth pulse. Reducing the dressing strength weakens the dressed interaction, so maintaining the target phase at the same pulse duration requires operation closer to the avoided crossing, where the Rydberg admixture increases. This dependence is then used to select the shortest gate at a fixed peak Rabi frequency in the Förster-enhanced operating range that accumulates the CZ phase with high Bell-state fidelity while keeping the Rydberg population small. Changing the Förster defect shifts the avoided crossing, while the gate parameters change only weakly. For a specific rubidium Förster channel, the selected gate corresponds to experimentally relevant laser coupling, pulse duration, and interatomic separation. We also estimate errors from the finite Rydberg lifetime and from weak excitation of a neighboring spectator atom. For the parameters considered, the spectator-induced error remains below the finite-lifetime contribution.

We exhibit a bipartite language with a poly-logarithmic quantum communication protocol and polynomial Merlin-Arthur communication complexity.

Mixed-state quantum geometry plays a fundamental role in quantum metrology, multiparameter estimation, and the characterization of quantum many-body systems. Yet, unlike its pure-state counterpart, accessing mixed-state geometry requires solving an ill-conditioned Lyapunov equation for the symmetric logarithmic derivative (SLD), posing a major challenge for resource-efficient quantum computation. Here we address the challenge and develop a novel quantum algorithmic framework for efficiently accessing the quantum Fisher information matrix (QFIM) and quantum geometric tensor (QGT) of mixed states. Our key insight is to uncover a previously unexplored connection between the positive semidefinite structure of density matrices and exponentially convergent Gauss-Laguerre quadrature, enabling an efficient integral-based construction of the SLD. A rigorous complexity analysis further establishes the resource efficiency of our algorithm, demonstrating logarithmic precision dependence and double-logarithmic ancillary-qubit overhead at fixed conditioning. Building on this construction, we achieve near-Heisenberg precision scaling for diagonal QFI estimation without quantum phase estimation and construct unified block encodings of the full QFIM and QGT under a bounded spectral-gap assumption. A complementary regularized algorithm extends efficient diagonal estimation to exponentially small spectral gaps under a bounded-response condition. Our results establish a resource-efficient route to coherent mixed-state quantum geometry, enabling its direct integration into quantum linear-algebra algorithms without classical reconstruction and opening new possibilities for quantum-enhanced multiparameter metrology.

Collective coupling to the Minkowski vacuum allows uniformly accelerated quantum detectors to exhibit a strong quantum Mpemba effect, in which a state initially farther from equilibrium relaxes faster than a closer one. We establish the existence of this effect for every fixed finite number of detectors $N\geq 2$ at sufficiently small transverse separation within the pointlike secular master equation. The mechanism originates from two reflection sectors whose populations are conserved by the leading collective dynamics. Weak intersector transfer at finite separation generates an isolated, parametrically slow relaxation mode. A simple family of initial states permits its leading-order cancellation by matching the equilibrium sector populations, while a corrected preparation eliminates the slow-mode amplitude exactly. We construct a reference state that establishes a genuine reversal of trace-distance ordering. Numerical calculations and local-rate-preserving controls identify the collective origin of the effect, while spatially smeared detector calculations support its persistence within the second-order secular framework. The same mechanism extends to detectors coupled to a common thermal field, with analytically distinct slow relaxation rates. Thus, strong Mpemba relaxation is not exclusive to acceleration but emerges from a more general interplay between collective dissipation, reflection-sector conservation, and weak symmetry-breaking transfer.

The geometry of momentum-space Hamiltonian maps derived from the zero-frequency single-particle Green's function provides a route to a refined topological characterization of quantum systems beyond the noninteracting clean limit. The central idea is to complement standard topological invariants by invariants that characterize the geometry of the map itself. As a paradigmatic example, we study the one-dimensional chiral Su-Schrieffer-Heeger model with disorder, where the topological Hamiltonian defines a planar Bloch loop. In addition to its conventional winding number, this loop possesses an integer turning number that characterizes the winding of its tangent vector. We identify turning-number transitions that occur while the topological Hamiltonian remains finite and spectrally gapped, driven solely by a vanishing tangent vector of the Bloch loop, and obtain an extended phase diagram with additional topological structure beyond the winding-number classification. Asymptotic analysis predicts the emergence and disorder dependence of the corresponding transition regime, in agreement with the numerical results. Our findings establish the geometry of momentum-space Hamiltonian maps as an additional source of topological structure beyond conventional classifications.

Fractional Chern insulators bring the fractional quantum Hall effect, with its anyonic excitations, to zero magnetic field. So far they have been realized in moiré materials, where the long superlattice period weakens electronic interactions and confines these phases to cryogenic temperatures. Early proposals instead envisioned topological flat bands on atomic-scale lattices, where fractionalization could persist to far higher temperatures, but a suitable material has been lacking. Here we theoretically identify monolayers of the recently synthesized van der Waals kagome family $\mathrm{A}_2\mathrm{T}_3\mathrm{X}_4$ as such a platform, combining intrinsic topological flat bands and strong Coulomb interactions with gate-tunable carrier density and layer assembly. Exact diagonalization of models derived from density functional theory reveals ferromagnetism over broad filling ranges, supporting diverse fractional Chern insulators, anomalous composite Fermi liquids, and charge-ordered phases. In particular, in $\mathrm{Cs}_2\mathrm{Pd}_3\mathrm{S}_4$, the fractional Chern insulator exhibits a many-body gap of approximately 26 meV in the largest system accessible with band mixing allowing at most one interband electron-hole excitation. Layer assembly further provides a natural route to fractional quantum spin Hall insulators: bilayers with antiparallel magnetizations support this phase at realistic separations. These results identify an experimentally accessible material family in which chemical composition, carrier density, and stacking offer complementary routes to fractionalization at enhanced energy scales and control over topological order.

Exchange-based two-qubit gates in semiconductor spin qubits are sensitive to low-frequency detuning noise and control errors. Here, we extend concatenated continuous driving (CCD), implemented by phase modulation of a global microwave drive, to exchange-based SWAP and $\sqrt{\mathrm{SWAP}}$ operations between double-dressed spin qubits and investigate its effectiveness for protecting two-qubit gates. We find that CCD retains strong protection against quasistatic common-mode detuning errors while substantially improving robustness against Rabi-frequency errors and qubit-to-qubit Rabi-frequency mismatch compared with conventional continuous dressing. By contrast, the gate fidelity is impacted by differential detuning errors. By modeling partially correlated quasistatic detuning noise, we further show that the noise-averaged gate fidelity depends strongly on the spatial correlation of the qubit-frequency fluctuations, with positive correlations enhancing CCD protection by suppressing the differential-noise component. These results identify the symmetry and spatial correlation of qubit-frequency noise as key factors governing continuous-drive protection in coupled spin-qubit systems.

Understanding the generation and activation of ergotropy, the maximum work extractable by cyclic unitary operations, is central to quantum battery research. Positive-temperature thermal states are passive, whereas nonequilibrium environments can sustain nonpassive steady states with nonzero ergotropy. However, the full secular approximation commonly used in Lindblad descriptions can suppress steady-state coherence and obscure its contribution to ergotropy. Using a Bloch-Redfield master equation beyond the full secular approximation, we investigate the ergotropy of the nonequilibrium steady state (NESS) of two exchange-coupled qubits connected to independent thermal reservoirs. The NESS ergotropy of two qubits with the same frequency is entirely coherent and grows quadratically with temperature bias near equilibrium. In contrast, detuned qubits can exhibit incoherent ergotropy. We derive an exact analytical criterion for its activation and show that activation requires the hotter reservoir to be coupled to the qubit with the higher bare frequency. Comparing NESSs obtained with and without full secularization reveals quantitative and qualitative differences in ergotropy that reflect changes in both its coherent and incoherent contributions. The results clarify the mechanisms of NESS ergotropy activation and demonstrate the importance of retaining steady-state coherence beyond the full secular approximation when characterizing stationary work resources.

We revisit the feasibility and convergence claims for the polarization hierarchy of Plávala, Ligthart and Gross [Linear Algebra Appl.\ 723 (2025) 15--32]. Counterexamples show that the stated assumption is insufficient for the feasibility characterization and for convergence of the hierarchy with the polarization constraint. We establish corrected results under a stronger algebraic condition and supply a missing compactness argument.

Let \(f = \text{EXACT}^5_{3,4}\) be the Boolean function that equals 1 exactly on inputs of Hamming weight 3 or 4. Earlier numerical studies reported success probabilities close to one using three queries, but the existence of an exact three-query algorithm had remained unresolved. This paper settles this problem by proving that the exact quantum query complexity of \(f\) is \(4\). For the lower bound, we express every three-query algorithm through layer-by-layer Gram matrices of low-degree Fourier coefficients. We then construct a fixed rational dual certificate whose slack matrices are all positive definite. This certificate separates the necessary Gram-matrix region from the exact-output condition and therefore rules out every exact algorithm using at most three queries in the stated model. The positivity verification reduces to five small rational matrices and Sylvester's criterion. For the upper bound, we invoke the previously known four-query algorithm for the seven-bit function \(\text{EXACT}^7_{3,4}\) and apply the standard padding reduction. To quantify the near-exact behavior, we use the same certificate to derive a valid, though not claimed tight, lower bound \(\frac{25600}{43779488192449}>0\) on the worst-case error of every algorithm using at most three queries. This positive error gap is compatible with the near-unit success probabilities reported in earlier numerical studies, which do not establish exact computation.

Quantum decoding succeeds when a correction matches the logical class of the error, whereas ordered-statistics decoding (OSD) searches a finite list of physical corrections. We connect these spaces through a rank-$k$ logical-signature map $M_{\rm log}:\mathbb F_2^q\to\mathbb F_2^k$. For fixed, error-independent orderings it yields the exact logical-signature distribution, the OSD-0 logical error rate, and the logical-class coverage of any fixed list. For minimum-cost list decoding we prove $P_L=P_{\rm miss}+P_{\rm sel}$, separating absent-class from wrong-selection failures. Hypergraph-product and bivariate-bicycle codes are consistent with the coverage predictions. On the $[\![144,12,12]\!]$ gross code, 672 coverage-aware candidates outperform 899 combination-sweep candidates (paired McNemar $p=0.013$), while two lists with identical logical coverage give $P_L=11.30\%$ and $3.78\%$; the signature-based coverage compression persists across 30 random column orderings. Logical coverage and within-class representative selection are therefore complementary resources that candidate count alone does not capture. The framework guides OSD list construction and compression by identifying coverage requirements and distinguishing coverage losses from failures of representative selection.

Multiparameter quantum Otto engines raise an optimization problem absent in single-parameter cycles: which small quench vector maximizes the quadratic approximation to the exact output work in a multidimensional control space? We develop a local response theory for sudden-quench Otto engines with quantum working media described by linearly controlled Hamiltonians. We show that the local quadratic work decomposes into a thermal-bias gain and a quadratic response cost, whose competition determines the quench vector that maximizes the local quadratic work at a prescribed quench amplitude. We illustrate the theory in a minimal two-level working medium, where radial and transverse quenches play distinct roles, and in a finite interacting XYZ spin chain, where the resulting quench vector is determined by the balance between thermal-bias and response cost. Our results provide a practical local criterion for designing small multiparameter quenches in sudden-quench quantum Otto engines.

Quantum correlation measurements have emerged as a powerful tool for localizing multiple emitters with subwavelength separation. Multi-emitter localization consists of two distinct tasks: identifying the emitter count $N$ and estimating their positions $\left\{x^{i}\right\}$. Existing fit-and-select frameworks fit the measured intensity and autocorrelation data using several models corresponding to different values of $N$ and then select the best-supported model. This procedure lets errors from the multi-parameter optimization of emitter positions propagate into the choice of model, degrading performance under photon-limited and high-background conditions. We propose a method that directly infers the emitter count and positions from the multimodal data via learned inference. Learned inference improves both the emitter-counting accuracy and localization precision compared to the fit-and-select method. It achieves more than tenfold improvement in precision and requires up to five times fewer photons to achieve practically meaningful localization with the largest gains observed under low photon counts, strong background, narrowly spaced emitter configurations, and spatially truncated data. This photon-efficient quantum-assisted localization framework offers a promising route toward real-time biological imaging and single-particle tracking in densely labeled samples.

Quantum entanglement is intrinsically nonlocal, whereas tunneling spectroscopy measures one site at a time. We show that this apparent mismatch can be overcome: local tunneling spectra can certify spin entanglement without coherent control or absolute intensity calibration. An exact spin sum rule turns the high-bias conductance into an internal normalization, allowing the inelastic spin-flip weight to place a lower bound on the local quantum Fisher information. Total-spin conservation then fixes the otherwise inaccessible intersite fluctuation, converting two local spectra into a bound on a collective entanglement witness. We incorporate coupling to the substrate through a spectroscopic bound on spin leakage, while a hierarchy of thresholds distinguishes entanglement between the spins from entanglement with their environment. Including instrumental broadening and noise, the resulting certificate holds at a stated confidence level. These results establish a route for extracting nonlocal quantum information from equilibrium local spectroscopy.

Understanding generalization is essential for assessing the practical viability of quantum machine learning. In many applications, quantum models operate on classical data that must first be encoded into quantum states, making the encoding part of the effective hypothesis class. We develop a margin-based generalization framework for this setting, covering both fixed and trainable quantum data encodings. For fixed encodings, the existing margin bound transfers unchanged. For trainable encodings, we derive a bound using a two-scale covering argument that combines the original margin-dependent term with an additive encoding-capacity term of order $\tilde O(\sqrt{L/m})$, where $L$ is the number of trainable encoding parameters and $m$ is the training-sample size. Across 19,440 simulated training runs spanning various image datasets, circuit architectures, and optimization settings, the inverse margin performs best among five baseline and two bound-derived complexity measures under conditional-independence and 90th-percentile sign-error criteria, within bootstrap uncertainty. These results provide a unified margin-based view of generalization in quantum machine learning with classical data.

In supervised quantum machine learning with classical data, classification performance critically depends on the geometry induced by quantum data embedding. Existing data-adaptive approaches rely on pairwise fidelity evaluations between samples, which scale as $O(B^2)$ for $B$ samples and create a computational bottleneck in iterative embedding optimization. To address this issue, we propose a prototype-guided framework for efficient data-adaptive quantum embedding. Using class-prototype separation and sample-to-prototype compactness, we derive a measurable lower certificate for class-ensemble distinguishability and construct a prototype-based objective requiring only $O(B)$ fidelity evaluations. We integrate this objective into an end-to-end pipeline that combines task-specific quantum circuit architecture optimization with continuous refinement of the data-embedding parameters. Across five benchmark datasets with up to 20 qubits, our method retains competitive quantum kernel support vector machine (SVM) performance while reducing fidelity-evaluation cost, with particularly strong gains over budget-matched pairwise optimization on T-MNIST. Geometric analyses examine how the learned embeddings relate to kernel alignment and classification margins, revealing dataset-dependent benefits and limitations. We further derive a prototype-based classifier in the reproducing kernel Hilbert space that provides an explicit witness for the SVM objective and a low-cost proxy for model selection, and extend the framework to multiple prototypes for multimodal class structures.

An orbital quantum sensor is more precise than classical and holds its information in a quantum state's superposition and entanglement, which classical measurement collapses. Learning on quantum-sensed data therefore requires a distributed system in which the data stay quantum from sensor to inference. We present EntangledEdge, the first system architecture to unify orbital quantum sensing and learning end-to-end, with a quantum data plane and a classical control plane. It routes each event to a channel-matched model in a capacity-diverse bank, adapts its detection threshold without labels, and aggregates across stations by hardware fidelity. Evaluated with a hybrid prototype (real quantum processors, simulated orbit-to-ground link) over satellite telemetry, EntangledEdge achieves high-quality inference at bounded per-event cost, improves quantum processor utilization, and scales with fleet size.

Fault-tolerant quantum applications depend on both decoded measurement information and a continuing supply of magic states. While an operation waits for either, its logical data require protection that produces more syndrome data and decoding work. Architects must provision the quantum and classical parts of the machine together, before complete systems are available to measure. FTWeave is a system-level simulator for this architectural exploration. It accepts OpenQASM 2/3 circuits, CUDA-Q Logical compiler artifacts, Stim circuits, and provider-derived physical inputs through adapters that preserve operation and measurement dependencies. Users bind these inputs to quantum resources, classical processors, memory, communication, and factory configurations. One event timeline determines application progress, resource ownership, and continuing protection. This supplies the system model needed to connect circuit and decoder evidence to application performance. Controlled demand studies and complete multiplier and Ising circuits show why the coupling changes provisioning decisions. A fixed-work approximation predicts a 3.55x multiplier speedup from additional factories where the coupled model gives almost none. Explicit ownership also changes useful capacity: increasing decoder workers alone has no benefit in a storage-constrained case, while increasing workers and feedback entries together gives 4.93x speedup. Selected color and hypergraph-product code mappings take 53-90% longer under decoder service variability, despite an unchanged mean. These comparisons identify useful resource combinations and distinguish protection work from the elapsed lifetime of quantum data.

We present a hybrid quantum-classical iterative refinement for the pressure-Poisson equation of the incompressible Navier-Stokes projection method on noisy quantum hardware. Rather than solving the pressure equation once per time step, we solve it repeatedly for the normalized residual and scale each quantum direction by a least-squares fit to the physical residual. As a result, the error of the quantum solve enters as a contraction factor $\sinθ_k$ of the residual rather than as an error floor. This removes the requirement of a state infidelity below $10^{-7}$ that was estimated for single-solve schemes. The hardware noise then sets the rate of convergence but not the attainable accuracy, and it is this change of the role of the quantum solve, not an improvement of the hardware, that allows the residual to converge. With a boundary-consistent staggered (MAC) discretization, the pressure residual equals the velocity divergence left after projection up to the factor $Δt/ρ$. On the IBM processor ibm_cleveland, a four-qubit ($16\times16$) problem reached a relative residual below $10^{-7}$ within eight to ten corrections in all 20 runs of a pre-registered experiment, whereas a single solve with a comparable number of shots stopped at 0.33-0.59. In a six-qubit ($64\times64$) pilot, all three runs reached the same tolerance in 13 corrections. On the IonQ Forte processor, a manufactured-solution benchmark reached $5.6\times10^{-8}$ in nine corrections. With the variational training itself carried out on ibm_cleveland, the residual fell to $5.6\times10^{-4}$ in seven corrections, below the pre-specified tolerance of $10^{-3}$, at the rate predicted by a noise model. To the best of our knowledge, these are the first converged pressure solutions obtained on quantum hardware.

For the first time, scientists have achieved strong coupling between light and long-lived acoustic vibrations in an optical fiber. Optical fibers are used in both classical telecommunications and quantum communication and could serve not only as connections between computing nodes but also as quantum processors themselves in the future. The results, published in Nature Physics, pave the way for new technologies in quantum signal processing.

Guest post by Sarah Schlotter and Adam R. Wichman describe how the U.S. Patent Office may treat domestic manufacturing as a factor affecting when it will hear a challenge to the patentability of an issued patent claim. The article goes on to recommend best practices for quantum companies to work with this. The post Manufacturing Announcements Can Influence Patentability Challenges: What Quantum Computing Companies Should Know appeared first on Quantum Computing Report .

Insider Brief QuEra Computing scientists will serve as co-principal investigators on three of nine teams selected for the US Department of Energy &#8216;s $37 million Quantum Computing for Computational Chemistry (QC3) program. The projects target high-temperature superconductors, ultra-strong lightweight magnets and hydrogen production, using quantum algorithms and computational methods to address energy-related materials and chemistry challenges. QuEra will contribute neutral-atom quantum hardware access and expertise in algorithm and architecture co-design, with the three-year program aiming to demonstrate major improvements over classical methods at approximately 100 logical qubits. PRESS RELEASE &#8212; QuEra Computing , the leader in quantum computing, today announced that its scientists will work with three of the nine teams selected for the Quantum Computing for Computational Chemistry (QC3) program at the Advanced Research Projects Agency for Energy (ARPA-E) to develop neutral-atom based modeling frameworks for complex materials and molecules. The three-year program, announced by the Department of Energy in March 2026, directs $37 million across the program performers. QC3 exists to close the gap between vendor roadmaps that are rapidly transitioning to expanded logical capabilities by the end of the decade but don&#8217;t yet clearly map to the resources required for published algorithms for energy-relevant chemistry applications. ARPA-E&#8217;s premise is that the gap closes through full-stack co-design, where improvements of two to three times at each layer of the stack compound into an order of magnitude overall. The program asks its teams to identify an application worth a quadrillion BTU of energy or a gigaton of CO₂-equivalent, and to pursue a scalable hundredfold improvement over classical state of the art, validated at approximately 100 logical qubits. QuEra &#8216;s updated roadmap targets 1,000 logical qubits by 2029, providing ample hardware cap

Insider Brief Anderon has released its first superconducting quantum Process Design Kit (PDK), providing design components for quantum devices and circuits on its 300mm wafer fabrication platform. The PDK includes components for qubits, signal routing, amplifiers and filters, alongside a reference design for coherence validation and electromagnetic parameters for simulation. Anderon is offering early access through a license agreement, aiming to help developers prepare superconducting quantum designs for fabrication. Anderon has released its first Superconducting Quantum Process Design Kit (PDK), the company said in a blog post . According to Anderon , the kit is meant to give quantum device and circuit developers a more efficient, standardized way to work. The company said it supplies designers with the basic building blocks for manufacturable designs on its 300mm wafer fabrication platform. Anderon tied the release to the growth of the quantum computing ecosystem. As that ecosystem scales, the post says, comprehensive design infrastructure matters as much as access to advanced process technology. The blog post states that the PDK covers Anderon ’s full portfolio of 300mm wafer offerings, which it lists as: Qubits for quantum information processing I/O components for signal routing and device connectivity Amplifiers and filters for high-fidelity quantum control and readout The kit also contains a reference design for baseline coherence validation, along with electromagnetic parameters for simulation. Anderon said the PDK is intended to narrow the gap between device innovation and scalable manufacturing, so developers can take quantum designs to fabrication more efficiently. Anderon is offering early access to its first-generation PDK. The company described this as a milestone in its commitment to building infrastructure for the next era of superconducting quantum computing. Access is available through a license agreement. Interested parties can contact the Anderon

Insider Brief Germany&#8217;s BMI, BMDS and BSI have published a national guideline for implementing the EU roadmap for transitioning to post-quantum cryptography (PQC). The guideline recommends completing migrations for high-risk systems by the end of 2030 at the latest and largely completing the broader transition by 2035. The recommendations call for clear migration responsibilities and deadlines, systematic quantum-risk assessments, early coordination with manufacturers and supply chains, and cryptographic agility. PRESS RELEASE &#8212; Quantum computers pose an increasingly real threat to the security of cryptographic methods and thus to cybersecurity itself. The Federal Ministry of the Interior (BMI), the Federal Ministry for Digital Affairs and State Modernization (BMDS) and the Federal Office for Information Security (BSI) are now jointly publishing the Guideline for the implementation of the EU Roadmap on Post-Quantum Cryptography for Germany. It stems from an initiative by EU member states that had put forward recommendations for an EU-wide coordinated transition to quantum-safe cryptography, so-called post-quantum cryptography (PQC). Objectives of the Guideline The national guideline is aimed particularly at federal, state and local governments, as well as organizations and companies, including operators of critical infrastructure. It provides structured recommendations for the transition to quantum-safe cryptography and confirms the timelines of the European Roadmap: high-risk use cases should be switched to quantum-safe methods as early as possible; for these systems, the migration should be completed by the end of 2030 at the latest. The entire transition should be largely completed by 2035. The measures recommended in the national guideline include, in particular, the establishment of clear responsibilities and binding deadlines for the transition, the consideration of post-quantum cryptography in accordance with the state of the art, the systematic a

Quantum computers represent a next step in the fast-paced evolution of technology. Using quantum bits (qubits), they have the potential to run certain calculations exponentially faster than conventional computers. However, developing and fine-tuning quantum computers requires an enormous number of repetitive tests. To accelerate quantum technology development, we need a method that can read quantum states at ultrafast speeds.

Insider Brief A &#8220;Quantum 101&#8221; session at the World Trade Organization, co-organized by the permanent missions of Israel, Singapore and Switzerland, introduced trade negotiators to quantum technologies and their implications for trade. Speakers from industry, academia and national programs said the most direct link between quantum and trade is encryption, which secures payments, letters of credit, customs filings and e-signatures. Panelists also pointed to concentrated supply chains, diverging standards and a possible &#8220;quantum divide&#8221; between countries as trade questions that are already emerging. The World Trade Organization&#8217;s (WTO) member delegations were told this week that the encryption underpinning international trade could be broken by quantum computers within roughly five years, and that the trading system has no shared definition yet of what it means to be &#8220;quantum safe.&#8221; The warning came at a one-hour session in Geneva, organized by the permanent missions of Israel, Singapore and Switzerland to the WTO. The panel was moderated by Dylan Barry, executive director of the von Neumann Commission. &#8220;We are not here to ask whether the WTO needs rules on quantum technologies,&#8221; Carolinn Hjalmroth, head of Israel’s Trade and Economic Mission to the WTO, Foreign Trade Administration , Ministry of Economy and Industry, told the room, adding, &#8220;We simply want to start to understand what is changing, what is realistic and what may matter for our economies.” Trade Runs on Encryption Miriam Shtilman-Lavsovski , a partner at Tal Ventures , gave the introductory talk before turning to the issue she framed as most important for trade. “Trade runs on trust and trust runs on encryption,” Shtilman-Lavsovski, said. “ And one of the main issues today is how do we encrypt what we have and how do we encrypt what we&#8217;re going to have in the future? It&#8217;s e signatures, letters of credit, customs, payment, etc.” She to

Insider Brief Google demonstrated magic-state cultivation on its Willow quantum processor, reducing state-preparation errors about 40-fold and reporting 99.99% logical fidelity, potentially lowering resource demands for error-corrected computing. The team used reinforcement learning to improve processor calibration and developed a measurement technique to avoid overstating the prepared states’ quality. Researchers transferred prepared states between two error-correcting codes, but larger demonstrations remain necessary, and a storage test produced errors about seven times higher than simulations predicted. Google researchers reduced errors in a crucial quantum computing resource about 40-fold, demonstrating a method that could lower the hardware demands of useful, error-corrected machines. The experiment, published in Science , showed that a technique called magic-state cultivation works on Google ’s Willow processor , according to a Google Quantum AI blog post written by Emma Rosenfeld, research scientist and Craig Gidney, quantum software engineer. The team reported producing states known as T-states with a logical fidelity of 99.99%, which is a measure of how closely a protected quantum state matches its intended form. The result addresses a problem in quantum computing that preparing these states could consume much of a future machine’s resources and leave less capacity for the calculations it is meant to perform. Google ’s demonstration moves a proposed way to reduce that burden from theory to hardware. The researchers were also able to transfer these prepared states between two forms of quantum error correction as an early test of whether the preparation method can connect with the architecture intended to support larger computations. The work does not necessarily establish that the resource problem has been solved at a practical scale. Ultimately, then, this looks to be an important, incremental advance toward practical quantum computing that demonstrates a w

The researchers in the Quantum Detection Microscopy group at CIC nanoGUNE, in collaboration with chemists at CiQUS of the University of Santiago de Compostela, have demonstrated that adding or removing a single molecule from a quantum chain can fundamentally change its interaction with a superconductor.

NVision Quantum Technologies is expanding from its commercial hyperpolarized MRI platform into quantum computing hardware with its new PIQC (Photonic Integrated Quantum Chip) molecular architecture. This strategy utilizes synthetic organic molecules with optically addressable spin states deposited on silicon photonic chips, aiming for a scalable, photonically-entangled gate architecture for fault-tolerant quantum computing. This expansion builds on their commercial success with their Polaris MRI systems and recent significant financing and project involvement. The post NVision Quantum Technologies Expands into Molecular Quantum Computing with Photonic Integrated Architecture appeared first on Quantum Computing Report .

Google Quantum AI has successfully demonstrated magic state cultivation on its Willow quantum processor, achieving a 40-fold error reduction and producing T-states with 99.99(1)% logical fidelity. This breakthrough addresses a major bottleneck in fault-tolerant quantum computing by significantly reducing the physical qubit footprint required for generating these essential states, directly validating Google's 2024 cultivation theory framework. The post Google Quantum AI Demonstrates Magic State Cultivation on Willow Processor in Science Milestone appeared first on Quantum Computing Report .

Insider Brief Terra Quantum has joined the QuEra Quantum Alliance, adding its quantum software, algorithms and enterprise application expertise to the neutral-atom quantum computing partner network. Terra Quantum &#8216;s TQ42 platform provides a cloud-based quantum software environment with a Python SDK, APIs and algorithms for optimization, quantum machine learning and simulation. The partnership aims to connect enterprise applications with QuEra&#8217;s neutral-atom hardware, as QuEra targets availability of its 256-logical-qubit Libra fault-tolerant quantum computer through Amazon Braket in 2028. PRESS RELEASE &#8212; Terra Quantum , a global leader in the development of quantum technologies and their industrial application, the leader in neutral-atom quantum computing, today announced that Terra Quantum has joined the QuEra Quantum Alliance, a global partner program dedicated to accelerating the development, deployment, and utilization of neutral-atom quantum computers to solve the world&#8217;s most challenging computational problems. Reinforcing the Applications Layer of the QuEra Quantum Alliance Terra Quantum is hardware-agnostic by design, developing proprietary algorithms and software rather than quantum processors. Its TQ42 platform, a cloud-based quantum software-as-a-service environment, gives developers a Python SDK, APIs, and command-line tools alongside a library of algorithms for optimization, quantum machine learning, and simulation. The company works with customers across financial services, manufacturing, pharmaceuticals, logistics, energy, and the public sector. As a member of the QuEra Quantum Alliance, Terra Quantum will gain access to technical expertise and go-to-market resources from QuEra as well as partnership opportunities with other, complementary alliance members. Both QuEra and Terra Quantum see their expanded partnership as an opportunity to shorten the distance between an enterprise use case and hardware designed to scale toward fa

EMode Photonix, a quantum integrated photonics software startup, has successfully raised $1 million in pre-seed funding. This investment, led by Ground State Ventures, will enable the company to expand its engineering team and accelerate the development of its enterprise software. EMode Photonix specializes in a multi-physics simulation platform for non-linear integrated photonic circuits, offering significantly faster modeling capabilities for various applications including quantum computing and optical sensing. The post EMode Photonix Raises $1M Pre-Seed Round Led by Ground State Ventures for Photonic Circuit Simulation Stack appeared first on Quantum Computing Report .

Abstract Recent advances in transmission electron microscopy (TEM) have opened the path toward spin resonance spectroscopy with single-spin sensitivity. To assess this potential, we investigate the quantum precision limits for sensing magnetic moments with free-electron probes. Using a scattering model where an electron wavepacket interacts with a localized spin, we study two metrological tasks: estimating the magnitude of the magnetic moment and discriminating the presence of a spin. The sensitivity for a given measurement setting is generally determined by the classical Fisher information, which we benchmark against the quantum bound optimized over all measurements. We find that conventional TEM imaging can saturate the quantum bound when backaction of the probe electron onto the spin state is negligible. We also find that, when backaction is relevant, one could do better by realizing a measurement of the electron's orbital angular momentum state. These results establish the quantum limits of spin sensing in TEM and guide the development of future experiments probing individual electron spins or nanoscale ensembles of nuclear spins.

Abstract We investigate the non-equilibrium work statistics originating from a sudden quench in a bosonic Josephson junction. In particular, by employing the Holstein-Primakoff approximation, the work statistics are analytically characterized in the weak-interaction regime, where the dynamics map onto a time-dependent quantum harmonic oscillator. For a junction initialized in the ground state of the pre-quench Hamiltonian, we demonstrate that the work statistics are governed by a negative binomial distribution, as occurs in fully-connected models driven across a critical point. Furthermore, we also consider initial superposition states containing quantum coherences in the energy basis. To characterize the corresponding work distributions, we employ Kirkwood-Dirac quasiprobabilities (KDQ). Even in the simplest case, when the junction is initialized in a superposition of the ground and second excited states, the KDQ distribution of work exhibits negative or complex values, reflecting non-classical features. Moreover, the coherence content of the initial state can be optimized to enhance the extractable work extracted from the quench, beyond classical bounds. Finally, we propose an experimental interferometric protocol to directly measure the characteristic function of the work distribution in experimentally accessible settings.

In this review, we examine the interplay of symmetry and quantum interference in the attosecond domain primarily through one- and two-electron photoelectron momentum distributions. Using our own work, we discuss how tailored laser fields provide control over dynamical symmetries, and how quantum-orbit methods make it possible to connect the resulting momentum-space structures to specific ionisation, propagation, and rescattering pathways. Particular emphasis is placed on ultrafast photoelectron holography and nonsequential double ionisation through recollision excitation with subsequent ionisation, where several distinct forms of quantum interference can be identified and manipulated. We also discuss how target properties, including the binding potential, orbital symmetry and parity, modify this mapping. Finally, we consider emerging opportunities offered by non-classical states of light, for which photon statistics and quantum fluctuations provide additional degrees of freedom for controlling symmetry and strong-field electron dynamics.

Quantum networks must deliver end-to-end entanglement whose fidelity meets application requirements, which typically requires entanglement purification along multi-hop paths. Existing scheduling approaches either purify at the link level or optimize end-to-end fidelity for a static set of requests, and do not capture concurrent requests competing for network resources over time. This paper studies concurrent entanglement purification scheduling in a time-slotted quantum network with heterogeneous links, in which requests compete for link capacity and quantum memories, and each request may be served by multiple parallel paths for increased reliability. We formulate a mixed-integer linear programming (MILP) scheduler that maximizes the number of scheduled requests, with max-min path allocation as a fairness criterion, and develop reinforcement learning (RL) schedulers based on DQN, PPO, and SAC, whose rewards balance request success against Bell-pair consumption. Simulations under varying network load, topologies and target fidelity thresholds show that the RL schedulers achieve the highest success rates, improving on MILP by up to 6% and on Progressive Filling and Greedy heuristics by 16.5% and 19.5% respectively, at the cost of higher Bell pair consumption and the deferral of a small fraction of requests. MILP, in contrast, achieves the highest fairness and the lowest Bell pair consumption in most scenarios.

The interplay between chirality and magnetism is a profound topic, spanning particle physics, condensed matter, chemistry and origin of life. In this paper, we study this interplay in the new antiferromagnet (AFM) UOTe, and we report a chiral superlattice route to spin-split topological phenomena from collinear antiferromagnetism. Pristine UOTe is a collinear AFM without Berry curvature or spin-split bands. However, we identify the spontaneous formation of a chiral superlattice in UOTe, which can be viewed as frozen chiral phonons at finite wave vector. When electrons move through the chiral superlattice, their orbital Bloch wavefunction and quantum geometry are modulated by the strong chiral superlattice potential, generating large Berry curvature in the chiral superlattice, which we detect by the nonlinear Hall effect. At 150 K, the chiral superlattice induced Berry curvature couples to the collinear AFM order, generating a giant anomalous Hall angle ~0.14 abruptly near $T_N$ that is among the largest in bulk magnets. Moreover, our spin Hanle precession measurement shows that the chiral superlattice also generates spin-polarized current from the collinear AFM, a long-standing goal in spintronics. We shed light on the supermodulation formation mechanism based on chemical ion size and physical interlayer-intralayer energy competitions, using which we propose a design principle to discover similar bond-mismatch superlattices, providing a chiral superlattice pathway through real space engineering of quantum geometry.

A cross-platform benchmark should be device-independent yet sensitive to imperfections accumulated during execution. Building on prior work, we formulate and validate a protocol through demonstrations based on generalized Svetlichny inequality violations (a simulation, rather than a loophole-free certification, of multipartite nonlocality) for larger subsystem sizes. We apply it unchanged to three processors, the trapped-ion Marmot and IBEX Q1 (both manufactured by AQT) and the superconducting Euro-Q-Exa System 1 (IQM), using identical GHZ-state circuits with fixed theoretical measurement settings from N=2 to N=10 qubits. Both trapped-ion processors sustain violations up to ten qubits, while the superconducting processor loses them beyond six qubits under unmitigated (raw) conditions; readout-error mitigation recovers violations up to eight qubits, with a substantial fraction of the degradation attributable to measurement imperfections. These processors provide a heterogeneous testbed for validating the protocol's cross-platform applicability and discriminating power, demonstrating its practicality as a common framework for assessing collective quantum performance.

Fault-tolerant quantum computing requires high-fidelity quantum gates that are resilient to control errors and device imperfections. Here, we develop energy-optimal control pulses for single-qubit gates that are simultaneously robust against frequency detuning and waveform inhomogeneities while also suppressing leakage outside the computational subspace. Combining the optimized pulse envelopes with an adaptive control scheme, we experimentally demonstrate optimal robust gates on a superconducting quantum processor. For a gate duration of 90ns, we achieve fidelities above 99.9% for the X gate and 99.6% for Hadamard-type gates. For the X gate, we maintain fidelities above 99.5% for simultaneous drive-amplitude variations up to 20% and qubit detuning up to 4 MHz. This robustness outperforms that of conventional Gaussian pulses by an order of magnitude, without much difference in peak gate fidelity. These results establish a route towards robust single-qubit control in large-scale quantum processors, advancing the development of fault-tolerant quantum computing.

Benchmarking quantum processors is a central task in every roadmap aimed at quantum advantage. Here, we discuss a benchmarking protocol based on the violation of the Svetlichny inequality, which is designed to simulate genuine multipartite nonlocality. We compare it with Mermin's inequality, and present the results of applying this framework to two different quantum processing units -the superconducting system Garnet (from IQM) and the ion-trap system Marmot (from AQT), testing different families of quantum circuits for three to five qubits under identical experimental conditions. We also run simultaneous triplet tests across the full register, including a comparison between GHZ and linear cluster states, to probe how Svetlichny-inequality violations depend on qubit location and calibration. Our results demonstrate that tests based on genuine multipartite nonlocality provide a powerful tool to characterize the collective performance of quantum devices and to guide their calibration and optimization.

We define string breaking by the midpoint electric field falling to half a flux unit. In the massive Schwinger model, an energy balance between intact string and screened configuration predicts this separation using only vacuum observables and meson masses as input. We observe numerically that this half flux point corresponds to equal weights of the two configurations thus explaining the observed peak of the entanglement entropy as maximal uncertainty of the binary flux. The same binary uncertainty explains the entanglement peak at the vacuum transition. Near breaking, screening organizes part of the spatial entanglement between the string interior and exterior into a nearly maximally entangled bit. Within the selected flux sectors, this approximate encoded Bell pair records whether the flux is screened and nearly separates from the remaining correlations. The vacuum transition exhibits the same structure. The string and the $θ$-vacuum reveal a matching structure of the capacity of entanglement minimum at their transition point, linking their entanglement spectra. The transition rearranges degrees of freedom coherently as revealed by the entanglement asymmetry and Robustness of Magic of disjoint subregions. Finally, we construct the $θ$-vacuum and string wavefunctions with high fidelity using a restricted Boltzmann machine ansatz.

Integrating condensed noble gases with superconducting circuits offers new opportunities for operating hybrid quantum devices. In particular, electrons on solid neon have recently emerged as exceptionally coherent charge qubits, however the growth of the underlying neon films on patterned devices remains poorly controlled. We monitor neon films near the triple point using a multimode resonator fabricated from high-$T_c$ YBCO, which remains superconducting at temperatures where the liquid phase exists and whose geometry sets a thickness-sensing window near 1 $μ$m. In the liquid state we observe rich film dynamics: uniform wetting that saturates near 20 nm, drainage of thicker films, and spontaneous thickness oscillations, reflecting the extreme sensitivity of thick films in this regime. A galvanic connection to our sensing volume enables in-situ electrostatic tuning of the liquid film thickness. Statistics of freezing the neon across various liquid levels reveal variations of the solid film thickness by approximately an order of magnitude. We also observe a two-fold increase in the quality factor of the resonators at the level of $10^3$ with added neon and rule out dielectric loss as the limiting factor. Our results demonstrate that hermetic packaging facilitates the investigation of both rich non-equilibrium fluid dynamics and the impact of condensed noble gas films on microwave loss in superconducting circuits, but may not be the best modality for growing solid neon films with precisely controlled thickness.

We introduce Trajectree, a quantum trajectory-based quantum circuit simulator that uses a novel, state-saving partial execution of the quantum circuits to simulate broad and deep noisy quantum circuits efficiently. Trajectree can efficiently generate a large number of Monte Carlo samples by saving partially executed trajectories. We conduct extensive performance analysis of the Trajectree approach, proving the utility of the trajectory saving scheme for simulations of open quantum systems. Using this architecture, we show that Trajectree can simulate standard benchmark noisy circuits over five times faster than Google's QSim, a part of the Cirq package. We also analyze Trajectree's performance for simulating quantum optical systems relevant to communication and computing applications. We demonstrate applications of the optical backend to simulate three optical experiments: CHSH Bell test, entanglement swapping, and optical CNOT gate. This shows Trajectree's potential for simulating noisy qudit and optical systems efficiently.

Many simulations of partial differential equations require the repeated solution of linear systems whose matrix remains fixed while the righthand side changes. We present a hybrid offline online framework for this setting. The discretized operator is organized into small coupled blocks and reduced through block Schur complements. Instead of expressing the complete PDE solution as one large binary optimization problem, quadratic unconstrained binary optimization is used only to construct reusable local inverse factors. These factors are computed during an offline stage, decoded and stored, and then reused in an ordinary classical block solve for subsequent righthand sides. The optimizer facing problem size is governed by the local block size and chosen numerical precision, rather than by the dimension of the full spatial grid. We develop the mathematical formulation, analyze the accuracy and resource requirements of the binary representation, and examine the method on representative finite difference PDE problems, including execution of the local optimization stage on quantum optimization hardware. The resulting architecture provides a reusable interface between conventional numerical linear algebra and QUBO based quantum optimization.

We construct translation-invariant pure quasifree fermionic states on the one-dimensional lattice whose half-chain von Neumann algebras are hyperfinite factors of type $\mathrm{II}_\infty$ or $\mathrm{III}_λ$ for any $0<λ\leq 1$. Via the Jordan-Wigner-Araki transformation, these yield translation-invariant pure spin-chain states with the same half-chain factors, demonstrating that such factors need not be of type I or III. Each state is the unique ground state of a gapless, translation-invariant parent Hamiltonian with superpolynomially decaying interactions. For any fixed factor type, the interval entanglement entropy can exhibit widely varying growth rates, from arbitrarily slow divergence to nearly power-law growth, showing that entropy scaling does not determine the factor type. In contrast, we prove that gauge-invariant quadratic Hamiltonians with finitely many flavours and exponentially decaying hopping exhibit a dichotomy: their ground states either satisfy an area law with a type I half-chain factor, or have logarithmic entropy growth with a type $\mathrm{III}_1$ factor. The counterexample was discovered with AI assistance.

Terahertz scanning near-field optical microscopy (THz-SNOM) enables spatially and spectrally resolved investigation of low-energy collective and topological states in quantum materials and nano-structured devices by exploiting the strongly localized near field generated by a polarized atomic force microscopy (AFM) tip. Because the THz near-field response is highly sensitive to tip geometry, understanding how geometric parameters control field confinement and decay is essential for selecting tip designs that provide the spatial resolution required for specific experiments. In this work, we develop a boundary element method (BEM) for modeling the electrostatic near-field of a conducting AFM tip in response to an external background field. The tip is represented by a simplified closed, blunt-cone geometry with its surface discretized into panels using increased mesh density near the apex. A modified Green's function is used to calculate interactions between surface panels, while an augmented linear system simultaneously enforces the equipotential boundary condition on the conducting surface and overall charge neutrality to determine the induced surface-charge distribution. We validate the BEM by comparing the resulting near-field decay with that obtained from a three-dimensional quasi-static COMSOL Multiphysics simulation. The BEM accurately reproduces the COMSOL field-decay behavior while requiring orders of magnitude fewer mesh elements and substantially reducing computational cost. These results demonstrate that the BEM provides an accurate and computationally efficient framework for systematically investigating the dependence of THz near-field confinement on AFM tip geometry. This framework can be extended to more complex and experimentally realistic tip geometries, providing a route toward rational tip selection and design for application-specific spatial-resolution requirements.

We report the cryogenic characterization of a 14-nm nMOS Forksheet transistor down to 10 mK. We demonstrate that the device retains transistor operation with improved characteristics at cryogenic temperatures, while also forming a gate-defined quantum dot that can be tuned to the single-electron regime. In the quantum-dot regime, we perform low-frequency charge-noise measurements across different charge occupations and observe an average charge-noise amplitude of $\langle S_0\rangle = 10\;μ\mathrm{eV}/\sqrt{\mathrm{Hz}}$ at 1 Hz, with a minimum measured value of $3.3\;μ\mathrm{eV}/\sqrt{\mathrm{Hz}}$. These results highlight the potential of Forksheet technology for the monolithic cointegration of quantum and classical CMOS functionalities in future quantum processors.

Quantum repeaters will be paramount to the success of the future quantum internet. Presently however, the losses incurred in fibre communications are unsustainable when fragile quantum states are transmitted over long distances. The most effective repeater nodes will require incorporation of a minimum of two quantum memory units (QMems) for successful operation. Therefore a network composed of numerous nodes will ideally require scalable repeaters that contain QMems that are portable, robust and do not require a high amount of overhead. Here we investigate the performance of a commercial QMem based on a warm vapour of Rb atoms. Specifically, we characterize the coherence time, absolute efficiency, signal to noise ratio and bit error ratio of this device over a range of vapour temperatures that are readily controllable. For our system, we place these performance metrics into the same conventions as those established for current optical communication protocols. Development of QMem systems meeting these benchmarks will be a vital step for seamless integration of QMems systems into present-day communication architectures.

We present a quantum simulation of the SU(2) lattice gauge theory in 1+1 dimensions with one flavor of fermions, performed using the trapped-ion Quantinuum System Model H2. This work is based on the loop-string-hadron (LSH) formulation of the gauge theory, and is distinguished by using qubits to represent both bosonic-gauge and fermionic-matter degrees of freedom. Furthermore, we access the $j=1$ electric-flux sector beyond the $j_{\max}=1/2$ truncation commonly used in SU(2) quantum simulations. To that end, we digitize an electric-field degree of freedom using a multiqubit register for representing the bosonic quantum number. Our simulation therefore synthesizes several key ingredients relevant to quantum simulations in higher spatial dimensions, in particular explicit local gauge-field degrees of freedom represented here by a multiqubit bosonic register, while relying solely on circuit-construction optimizations that are expected to scale polynomially with lattice size. This work demonstrates that modern quantum hardware is increasingly able to accommodate the features of complicated but physically important lattice gauge theories while successfully reproducing the expected Trotterized dynamics.

Quantum error correction enables scalable fault-tolerant quantum computation by suppressing logical errors exponentially with code distance once physical error rates fall below a critical threshold. Here we demonstrate below-threshold operation of triangular color codes with distances $d=3,5,$ and $7$ on Quantinuum's Helios trapped-ion quantum processor. Leveraging both circuit- and hardware- level leakage reduction schemes, we achieve logical error rates as low as $5_{-2}^{+4}\times 10^{-6}$, and demonstrate error suppression by over an order of magnitude, $Λ=12_{-2}^{+3}$, with each successive increase in code distance. Moreover, we demonstrate below threshold scaling of error rates for Clifford two-qubit randomized benchmarking circuits when encoded in $d=3,5$ color codes, achieving logical error rate of $7^{+3}_{-3}\times 10^{-5}$ per logical two-qubit Clifford at distance $5$ with a suppression factor of $Λ=9_{-3}^{+8}$. We compare logical performance for existing near-optimal algorithmic decoders, and both convolutional neural network and transformer-based neural network decoders capable of real-time decoding an order of magnitude faster than the syndrome extraction rate. These results approach the logical error rates required for megaquop-scale quantum computation and indicate that scaled trapped-ion processors could reach application-relevant performance with substantially smaller code blocks than indicated by previous results in other qubit modalities.

Georgiev's analysis of a freely precessing spin correctly emphasizes that the Mandelstam-Tamm quantity $ΔT=Δ\hat A/|d\langle\hat A\rangle/d t|$ is not the variance of a time operator. He concludes, however, that its divergence near the extrema of the clock signal is devoid of physical meaning and that $ΔT$ does not disclose how well the system measures the passage of time. For the same projective $\hatσ_x$ readout, we show that $ΔT$ equals the inverse square root of the classical Fisher information in one binary outcome at regular operating points. Its divergence at submaximal-coherence extrema therefore identifies a loss of local sensitivity in the selected readout, not an infinite variance of physical time; a complementary $\hatσ_y$ measurement remains informative. This interpretation also separates Georgiev's exactly known tick--tock period from the statistical precision with which a tick can be located. It preserves his warning against a time-operator interpretation while qualifying his stronger conclusion that the Mandelstam--Tamm scale lacks physical content.

For given control channels, quantum control theory determines whether quantum gates can be realized, but not their resilience to errors. We address this problem by establishing existence criteria for robust gate implementation in $d$-level systems. Our criteria reveal that implementability of all gates is not enough: a universal family of robust gates exists if and only if the driven Hamiltonians share no common symmetry. When these criteria hold, we can make gates resilient to any combination of static perturbations, uniform Hamiltonian rescaling, perturbations at a finite set of selected frequencies, and perturbations with arbitrary selected waveforms. We can impose robustness conditions broadly with limited information about errors, e.g., against any static perturbations; we can also tailor these conditions to the platform, e.g., against environment-induced noise with dominant spectral peaks, requiring no spectral details beyond the peak frequencies. We numerically construct explicit protocols for robust gates, reducing average gate infidelity by approximately two to seven orders of magnitude under Hamiltonian perturbations and environment-induced noise. Together, our existence criteria and numerical constructions provide practical guidance for evaluating the potential of quantum platforms and designing robust quantum gates.

Quantum error correction can suppress logical errors exponentially with code distance when physical noise is below threshold. Realizing this on hardware requires tight coordination among quantum gates, mid-circuit measurements, and qubit coherence. Device variation, noise asymmetry, and correlations across space and time complicate the translation of these capabilities into logical error suppression. Here, we study rotated surface-code memory on an IBM Nighthawk r2 processor. Performance varies across tested processor placements, which we attribute to differences in qubit quality. We optimize the code by combining short readout, fused measurement and reset, and an XX echo on data qubits during ancilla readout. Compared with standard readout without reset or echo, the optimized syndrome extraction circuit reduces the median per-round logical error rate by factors of 3.8 in the X basis and 1.4 in the Z basis. In memory experiments of up to 150 rounds, the distance advantage weakens, alongside long-lived correlations that may reflect a persistent error component. Under our optimization recipe, increasing the protected distance from 3 to 6 while holding the other distance fixed reduces the per-round logical error rate from 0.53% to 0.24% in Z memory and from 0.52% to 0.22% in X memory. The corresponding error-suppression factors under maximum-likelihood decoding are 1.68 and 1.85. These results connect circuit compilation and optimization to surface-code memory performance and limitations, and motivate QPU and QEC circuit codesign for fault-tolerant quantum computing primitives on current cloud hardware.

Parameterized quantum circuits are widely investigated in quantum machine learning, yet how their architecture can provide task-aligned inductive biases remains poorly understood. We study data reuploading quantum circuits with two distinct inputs: a signal that varies between samples and a fixed, task-defined spectral query that specifies how the signal should be probed. We show that encoding the query can change the circuit's hypothesis class over the signal by modulating how its existing signal frequencies are combined, without introducing new sample-dependent information. This mechanism matches tasks built on nonuniform Fourier transforms, whose evaluation frequencies specify the query and whose sampling positions guide its encoding. We examine this connection in a classification task inspired by synthetic aperture radar, where acquisition geometry determines a query for classifying unfocused spectral patches before image formation. Across small-scale spectral and radar-like tasks, aligned queries improve learning from limited data over parameter-matched circuits with mismatched or absent queries. These results provide a route from known spectral task structure to the design and validation of inductive biases in parameterized quantum circuits.

We discuss an effective paradigm of utilizing AI agents to better compile quantum circuits when one can constrain bottleneck subroutines to have some form of classically verifiable structure. For example, when critical subroutines are composed exclusively of reversible classical logic, phasing operations, and measurement based uncomputation, one can efficiently simulate execution for classical inputs. This property facilitates efficient certification of approximate circuit synthesis via a form of fuzz testing, provided suitable assumptions on the input distribution. While this pattern was recently exploited to improve quantum cryptanalysis circuits, here we highlight the flexibility of the broader approach by discussing three important applications. (1) The computation of $1/\sqrt{x}$ that bottlenecks real space simulations of the Coulomb operator such as those important for modeling inertial confinement fusion reactors. (2) The decoding of Reed-Solomon codes which bottlenecks the decoded quantum interferometry algorithm when used to approximately solve the optimal polynomial intersection problem. And (3) the quantum look-up tables and controlled application of Givens rotations that bottleneck the most performant quantum algorithms for simulating chemistry in second quantization. We discuss reference implementations of these algorithms and how they can be constrained and verified in the interest of seeding a Kaggle competition designed to accelerate AI-based research into the optimization of their compilation.

Future quantum networks will rely on control-plane decisions such as routing, scheduling, entanglement provisioning, purification, and memory allocation. Each decision depends on a timely and reliable estimate of the quality of the entanglement that a candidate path can deliver, with end-to-end fidelity as a central metric. Inspired by the optical-networking experience with quality-of-transmission (QoT) estimation, this article asks when a quantum controller should compute fidelity analytically, simulate it, or learn a surrogate model. The optical analogy is useful but incomplete: optical QoT estimation often predicts a scalar transmission margin, whereas quantum QoT estimation must account for probabilistic entanglement generation, random memory waiting times, decoherence, state consumption, and measurement constraints that can make fidelity a stochastic target. We propose a compute/simulate/learn framework for quantum QoT estimation and illustrate it with a simulation-based proof of concept. Our study shows that analytical composition can be sufficient in simple regimes, that simulation becomes necessary when stochastic memory effects shape the delivered fidelity distribution, and that lightweight learned surrogates can approximate simulator labels at much lower runtime cost for online control. We close with open challenges for deployment, including stochastic targets, sim-to-real transfer, data-generation cost, physics-informed learning, and generalization beyond individual paths to full network topologies.

The macroscopic behavior of a non-interacting gas of Abelian anyons has remained unsettled for many decades. Prior numerical methods employing exact diagonalization in the continuum and on the plane have been limited to small system sizes, at most $N = 4$ anyons. Using the rapidly developing technology of neural network wavefunctions, we develop variational ansatze appropriate for studying continuum models of the Abelian anyon gas. The neural network architecture, which we call "AnyNet", is capable of exactly enforcing the non-analytic short-distance behavior induced by the anyonic statistics. We demonstrate excellent agreement with exact diagonalization for $N=4$ anyons, obtain accurate results up to $N = 16$ for intermediate statistics, and study up to $N=20$ for almost-fermionic anyons, matching perturbative results within a 0.4% discrepancy. We use this methodology to study anyons in a harmonic trap, and anyonic atoms as a model for anyon binding to impurities. We study the structure of anyonic wavefunctions as the statistics parameter is varied. We focus on the single-particle density, the pair density, the angular momentum, and the scaling of the wavefunction as multiple anyons coalesce. This work opens doors to understanding the macroscopic behavior of anyons, for which rich phases have been predicted theoretically.

Superconducting travelling-wave parametric amplifiers (TWPAs) provide broadband gain, low added noise, and high dynamic range, making them attractive for applications requiring wide instantaneous bandwidth. This is crucial for amplifying multiplexed narrow band signals spread over a wide frequency range, such as qubit resonator arrays, or amplifying inherently wide band signals, such as in spectrometers or radiometers. In many cases, however, the useful bandwidth of a TWPA is limited by the production of the idler tone at an image frequency. For three-wave-mixing (3WM) TWPAs, for example, an input signal at $f_s$ is indistinguishable from one at $f_p - f_s$, which can produce spectral ambiguity when the input spectrum is broadband or not known in advance. We experimentally demonstrate a balanced architecture that doubles the instantaneous image-rejected bandwidth available to a 3WM TWPA by spatially separating the amplified signal from the output pump and generated idler, which resolves the sideband degeneracy. The architecture consists of two amplifiers connected between a pair of 180$^{\circ}$ hybrid couplers, with the signal and pump injected and output through the sum and difference ports, respectively. Using two kinetic-inductance TWPAs, we demonstrate approximately 20 dB of signal gain across nearly an octave of bandwidth, together with pump rejection below --20 dB and an average image rejection of approximately --15 dB over the operating band. These results establish balanced TWPAs as a practical approach to broadband parametric amplification, enabling improved contamination free bandwidth and eliminating the need for complex filtering.

We investigate the effects of spatially localized conserved quantities on transport and thermalization in quantum and classical many-body systems. We consider several related models: the integrable quantum Volterra model, its nonintegrable classical limit, and two cellular automata derived from the latter. Although localized constraints are often associated with lattice gauge theories, our models do not admit such an interpretation. In systems with discrete degrees of freedom, these constraints induce uniform fragmentation of the Hilbert or configuration space. In the quantum Volterra model, we derive an exact mapping of the dynamics within each Hilbert-space fragment onto a quantum chiral Potts chain. We find that energy transport is ballistic, with identical transport coefficients across all fragments. In the nonintegrable classical limit, energy transport is diffusive, and we similarly find the diffusion constant to be independent of whether or not the constraints are fixed (resolved). Finally, in the cellular automata, we show that, despite leaving transport unaffected, localized constraints lead to a strong breakdown of local ergodicity.

Altermagnets combine vanishing net magnetization with momentum-dependent, nonrelativistic spin splitting, offering functionalities attractive for spintronics and quantum devices. Their practical use, however, is constrained by the limited availability of materials that simultaneously possess the required altermagnetic symmetry, semiconducting electronic structure, and weak spin-orbit coupling. Here we show that these requirements can instead be separated between constituent materials through proximity engineering. We develop an analytical theory for a conventional semiconductor coupled to a gapped $d$-wave altermagnet and demonstrate that virtual tunneling transfers the altermagnetic spin splitting to the semiconductor. Crucially, the induced nonrelativistic and relativistic spin splittings exhibit qualitatively different dependences on band alignment. Virtual processes involving the valence and conduction bands of the altermagnet can reinforce the altermagnetic splitting while contributing with opposite signs to the interfacial Rashba coupling. Consequently, electrostatic tuning can access a regime in which the Rashba splitting vanishes while a sizable $d$-wave spin splitting persists. Exact diagonalization of the full heterostructure model confirms the analytical theory and establishes the robustness of this mechanism beyond the perturbative regime. Our results identify altermagnetic proximity as a route for engineering nonrelativistic spin-split electronic states in established semiconductor platforms, providing a general strategy for disentangling magnetic and relativistic spin interactions in quantum heterostructures.

The system-size scaling of bipartite entanglement can be used to detect phase transitions. We develop a related approach for strongly correlated electron models where large density matrices or large system size scaling are inaccessible. To this end, we demonstrate that phase transitions of various kinds are signaled by a sharp signature in the first- or second-order logarithmic derivatives of the negativity measuring entanglement between small clusters at varying distances. Crucially, we show how to mitigate the effect of quantum Monte Carlo noise at large distances when computing the negativity. Our focus is on the $t'$-$π$-flux Hubbard model using auxiliary-field quantum Monte Carlo simulations. It has the particular advantage of showing three distinct phase transitions in a single model: semimetal to band insulator, semimetal to antiferromagnetic Mott insulator, and a magnetic order-disorder transition belonging to the Gaussian, Gross-Neveu, and O(3) Wilson-Fisher universality classes, respectively.

The helicity of a magnetic skyrmion in a centrosymmetric frustrated magnet is a soft collective coordinate and a candidate variable for encoding quantum information. Its coherence is ultimately influenced by coupling to the magnon environment, which is commonly incorporated only phenomenologically. Here we combine a microscopic Keldysh treatment of the helicity--magnon coupling to resolve the contribution of individual magnon modes to the effective helicity dynamics. In the U(1)-symmetric model, the magnon bath generates, to leading order, a reactive helicity mass renormalization. When U(1) symmetry is broken, additional direct helicity--magnon couplings become allowed. In the presence of finite magnon lifetimes, these couplings generate an Ohmic contribution to the low-frequency helicity dynamics. The spatial symmetry of the perturbation determines which magnon sectors contribute to this damping, providing mode-resolved selection rules for the helicity--magnon coupling. Thus, we establish a microscopic connection between helicity dynamics and the excitation spectrum of frustrated skyrmions and identify the symmetry constraints governing dissipation of helicity-based quantum states.

We introduce Recursive Operator Localization (ROL), a framework for constructing hierarchies of local energy problems linked by linear maps between Hilbert spaces. To address spectral-gap problems, including those arising in quantum systems, we study a realization of ROL by nested subspaces indexed by a weighted simplicial complex. Using spectral gaps of auxiliary classical random walks on links, we propagate geometric estimates upward and use them to turn local spectral gaps at the bottom of the hierarchy into a spectral-gap bound for the global operator. For weighted scalar-valued functions on facets, the ROL decomposition becomes the law of total variance, recovering classical spectral-gap bounds from local link expansion (Alev and Lau, STOC 2020). Moreover, for positive binary spin distributions, conditional influence describes the overlap of the corresponding subspaces, yielding known heat-bath gap bounds from spectral independence (Anari, Liu, and Oveis Gharan, FOCS 2020). The framework also offers a route toward quantum Gibbs sampling, with applications requiring model-specific geometric estimates and energy comparisons.

Quantum kernels are among the most promising methods in quantum machine learning, providing a natural way to embed data into high-dimensional Hilbert spaces via quantum circuits and capturing non-linear relationships in data. Their learning behaviour is governed by the function class they represent, which is formally characterized by the structure of the associated Reproducing Kernel Hilbert Space (RKHS). However, a theoretical characterization of this function class, and of how it depends on the choice of feature map and its hyperparameters, is still lacking. In this work, we focus on the Instantaneous Quantum Polynomial (IQP) feature map and derive a Fourier representation of the associated RKHS generators as finite sums of trigonometric functions evaluated on polynomially transformed input variables, with a finite set of accessible frequencies determined by the circuit construction and scaled by the bandwidth hyperparameter. This representation identifies three bandwidth regimes with qualitatively distinct expressive properties from localised, through multimodal, to periodic. Numerical experiments on synthetic datasets with controlled periodic and multimodal structure, across data dimensions and feature-map configurations, reproduce the three regimes in both supervised classification and unsupervised anomaly detection, benchmarked against a classical Gaussian kernel. These results make the relationship between expressivity and data structure explicit for IQP kernels: expressive power translates into a practical benefit only when the accessible frequencies match with the structure of the data, which provides a criterion for selecting the bandwidth when the periodic or multimodal structure of data is known.

Quantum simulations of lattice gauge theories with continuous gauge groups require a choice of basis (how states of the gauge theory map to the qubit computational basis) and truncation scheme (which of the infinitely many gauge theory basis states should be omitted in the map to the finite dimensional qubit Hilbert space.) The most common choices are adapted to an electric basis for the gauge theory, where the basis states for each link are associated with irreducible representations of the gauge group. Electric bases and truncations are generally advantageous for preserving gauge symmetries and simulating the strong coupling regime, but their effectiveness in the weak coupling regimes of physical interest are less well understood. In this work, we compute relative probabilities $p(R')/p(R)$ for finding a link in the irreps $R,R'$ in the ground state of SU(3) lattice gauge theory using Euclidean Monte Carlo methods and weak-coupling lattice perturbation theory. The observables that compute these relative probabilities are constructed by introducing seams into an anisotropic lattice, and by a similar construction we are also able to measure relative probabilities of different site singlets (ways that electric flux braids together into a gauge singlet) at each vertex. With these methods we can quantify, for example, the importance of higher electric flux states in the weak coupling ground state. These results directly inform what truncations are needed to accurately capture non-abelian gauge dynamics near the continuum limit.

Low-resolution digital-to-analog conversion can simplify continuous-variable quantum key distribution (CVQKD) transmitters, but coarse quantization increases excess noise and can generate data-correlated spectral replicas. We demonstrate digital delta--sigma modulation (DSM) for low-resolution waveform generation in Gaussian-modulated CVQKD. In a 500-MBaud CVQKD system over 20~km of fiber, 3-bit second-order DSM achieves an estimated asymptotic secret key rate of 46.38~Mbps at an oversampling ratio of 12, whereas uniform quantization yields no positive rate. With 4-bit second-order DSM, the rate reaches 50.11~Mbps, approximately 97\% of the 12-bit reference. A noise model combining the DSM noise-transfer function with matched filtering guides the sampling-rate and signal-band design for effective noise suppression. We also identify a phase-conjugate spectral replica arising from third-order intermodulation between the pilot tone and quantum signal, and evaluate its key-rate penalty using a linear-replica security model. At 3-bit resolution and an oversampling ratio of 24, first-order DSM reduces the experimentally estimated leakage-mode strength by approximately four orders of magnitude. Together, our findings establish the security boundaries and operating conditions of DSM, providing design guidance for low-resolution CVQKD transmitters.

Separation of variables in Schrödinger equation allows an infinite-dimensional family of physically distinct field configurations that are dynamically indistinguishable in one selected sector, labeled by a conserved quantum number, while differing in all others. We call such a symmetry a partial isophase symmetry. Two main examples are considered: axially symmetric magnetic backgrounds (a rigid spectral flow of the Fock--Darwin oscillator, purely magnetic isophase families, and a two-channel extension) and a Cartesian slab geometry (magnetic barriers in two-dimensional electron gases, treated in the Appendices). We further discuss the consequences of this symmetry for the inverse spectral problem and consider its quasiclassical counterpart.

We study which input-output behaviours of several agents can be produced by a declared communication schedule, that is, a fixed sequence of senders, recipients, message alphabets, and output times, together with shared randomness. Since a schedule admits only finitely many deterministic protocols, membership is a linear program, and an infeasible target is excluded by a separating inequality. Under explicit operational assumptions, we prove that the affine hull of the achievable behaviours is described exactly by the equalities stating that each joint output statistic depends only on the inputs that can reach the agents involved, so that a violated equality identifies both the statistic and the missing input. One binary message per event already attains this affine hull, so message capacity restricts which behaviours are achievable without being visible to any equality. We apply the result to one-bit broadcast and relay hierarchies for two and three agents, and to low-order projections of the local polytope.

We study how a second qubit can improve the estimation of spin-environment parameters when only one of the two qubits is measured. Both qubits are coupled to a common spin bath through the exactly solvable central-spin model, in which populations and coherences both evolve. Because the bath operator coupled to the qubits commutes with the bath Hamiltonian, the environment induces no effective interaction between the qubits. Without initial correlations or direct inter-qubit coupling, the two-qubit probe therefore performs exactly like a single qubit. When initial system-environment correlations are included, preparing the second qubit reshapes the environment statistics in a parameter-dependent way, and the measured qubit reads out this imprint. This improves the quantum Fisher information (QFI) for the coupling strength by factors of 3-4 relative to a correlated single-qubit probe, and by more than an order of magnitude relative to an uncorrelated one. For temperature estimation, the improvement reaches a factor of about 8. A direct Ising coupling does not help by itself, but the advantage persists in its presence. We also derive the classical Fisher information for arbitrary projective measurements and identify the measurement that saturates the QFI, which in general lies out of the equatorial plane of the Bloch sphere.

In parity-time (PT)-symmetric non-Hermitian systems, an exceptional point, where eigenvalues and eigenvectors coalesce, typically separates a real spectrum from complex-conjugate eigenvalues. In logarithmic conformal field theories (LCFTs), such an exceptional point appears in the spectrum of scaling dimensions. Holographic models of LCFTs, such as the dipole model, are built exactly at this point. Here, we deform the holographic dipole model so that its two coalescing scaling dimensions split into either two real ones or a complex-conjugate pair. We obtain the renormalized two-point functions in closed form. They change continuously from a linear combination of two power laws, through the logarithmic form of the LCFT at the exceptional point, to log-periodic oscillations. For any pair of scalar primary operators with real mixing under dilatations, the conformal Ward identities fix this form up to two normalization constants, which the holographic dictionary determines. In PT-symmetric theories with such a dilatation operator, real and complex-conjugate scaling dimensions correspond to the PT-unbroken and PT-broken phases. In the BTZ black hole at finite temperature, the difference between the quasinormal frequencies associated with the two scaling dimensions changes from purely imaginary to purely real across the real-to-complex spectral transition. Correspondingly, the linear response changes from overdamped to underdamped, with critical damping at the exceptional point.

We open the quantum baker map with a position window of width $w$ and center $q_c$. Classical pruning tiles the $(q_c,w)$ plane into diamonds where the $T$ leading resonances form root-of-unity multiplets. At $w=1/2$ one periodic orbit survives for almost every $q_c$, and the multiplets are quantized without free parameters: their modulus $2^{-1/2}$ saturates the pressure bound and their phase is the orbit action. They form cycling multicomponent cat states, and the opening becomes one mid-circuit measurement, enabling spectroscopy with $\sim10^2$ shots on quantum processors.

We prove that a quantum walker cannot search a two-dimensional lattice in Grover's $O(\sqrt N)$ time, resolving the long-standing open question posed by Aaronson and Ambainis in 2003. A walker that hops between neighbouring sites of an $L\times L$ lattice, $N=L^2$, needs $Ω(\sqrt{N\log N})$ local steps at least to find a marked vertex, even with unlimited memory and free queries. Hence, Tulsi's algorithm is asymptotically optimal. Our proof rests on a surprising correspondence with classical electrostatics. We treat the marked vertex as a point charge and weight the overlap between the walker's states with and without the mark by the potential drop, which vanishes where queries act. Only local steps change this weighted overlap, at a rate limited by the field energy, so the lower bound is set by the self-potential of the charge. In the plane this self-potential grows logarithmically with system size, like the Coulomb potential, leading to the extra root-logarithmic factor. Several marked vertices turn the charge into a conductor, and the lower bound depends on their arrangement through its capacitance.

The success of long-distance quantum communication will hinge on quantum repeater nodes equipped with robust and scalable quantum memories. Such memories must possess specific operating characteristics to make these nodes practical. An attractive option for these memory devices is an atomic warm vapor system operating under the conditions of electromagnetically induced transparency (EIT). These systems are easy to implement and require relatively low equipment overhead. A key metric in atomic-based quantum memory performance is optical depth, as it is closely tied to the strength of light-matter coupling. Here, we simulate and measure the optical depth-based performance of an EIT quantum memory using a warm atomic vapor cell. We then translate the simulated and measured optical depth and efficiency metrics into expected entanglement distribution rates. Our analysis evaluates the feasibility of these memories in optical quantum repeater nodes, which are essential for robust long-distance quantum communication.

Bayesian inference enables self-consistent plasma parameter inversion in tokamak integrated data analysis by fusing multi-source diagnostics. However, under nonlinear Gaussian likelihoods, finding the maximum a posteriori (MAP) estimate typically relies on sampling methods whose high computational overhead precludes real-time plasma control. To address this bottleneck, we propose a Bayesian inversion framework using a Coherent Ising Machine (CIM)-a quantum computing architecture based on coupled degenerate optical parametric oscillators (DOPOs). With native all-to-all connectivity, the CIM directly maps the negative log-posterior potential onto a spin Hamiltonian and leverages quantum vacuum fluctuations for rapid state-space search during pitchfork bifurcation. Validated on plasma current profile inversion for the EAST tokamak, this method achieves a single-run solution time of approximately 1 ms. Although current qubit limits necessitate a block-wise iterative scheme that prevents full real-time execution today, rapidly scaling quantum hardware offers a clear pathway toward real-time tokamak control.

We demonstrate a fully fibre-integrated source of broadband polarisation-entangled photon pairs at telecom wavelengths based on a commercially available Zn-indiffused MgO:PPLN ridge waveguide incorporated within a Sagnac interferometer. Operating across the full degenerate SPDC spectrum using pump-suppression filtering only, the source exhibits a measured bandwidth of approximately 67 nm. Strong non-classical correlations are observed, with an average two-photon interference visibility of 96.9 +/- 0.2 %, a fidelity to the Phi + Bell state of 78.1 %, and a CHSH Bell parameter of S = 2.501 +/- 0.005. We further explore the effect of increasing source brightness on Bell-state performance, revealing the limitations of accidental-corrected metrics in high-flux operating regimes.

We study how to compute $f(A)b$ on a quantum computer, where $A$ is Hermitian. When $f$ is nonsmooth or has localized difficulty in the spectrum, classical numerical linear algebra approximates it with rational functions rather than polynomials. We propose the Cayley transform, parameterized by $σ\in \mathbb{R}$ and $γ> 0$, as an alternative to the standard quantum access model. The two parameters let one concentrate accuracy where $f$ is difficult, which standard models can achieve only by raising the polynomial degree globally. This transformation converts Hermitian matrices to unitaries, allowing generalized quantum signal processing to apply Laurent polynomials bounded on the unit circle. We compare three access models (block encoding, matrix exponential, and Cayley encoding) in terms of query complexity and of the cost of their circuit realization. When the difficulty of $f$ is localized in the spectrum, the Cayley encoding reduces the required degree by a factor of three to four, and it represents the shifted resolvent exactly at degree one. For spectral projectors, the standard models cannot reach the target accuracy at fixed degree, because their approximants cannot concentrate resolution near the discontinuity. Realizing the Cayley encoding from a block encoding requires solving a shifted linear system, whose cost offsets its query-complexity gain over the standard models. For structured matrices arising in practice, however, low-depth circuits for the encoding can be constructed directly, and the gain is preserved at the circuit level.

Deploying quantum neural networks (QNNs) on sparse hardware requires preserving task accuracy while reducing compiler-induced two-qubit gates, SWAPs, and depth. We present ConQUESTA (\underline{C}onstrained \underline{Qu}antum \underline{E}ntangler \underline{S}election with \underline{T}opology \underline{A}wareness), a post training pruning framework that combines task saliency with compiler cost, screens candidate entanglers, and searches complete pruning masks under an explicit accuracy constraint. Unlike one-shot ranking, each mask is transpiled as a whole across multiple coupling topologies. Across 4-, 6-, and 8-qubit QNNs and eight model seeds at 55% pruning, ConQUESTA achieves mean resource reductions of 61.6% on Breast Cancer, 72.0% on Digits01, and 82.2% on Iris, exceeding the strongest matched simple baseline by 3.5, 1.7, and 8.9 percentage points, respectively. Fixed-mask recovery raises feasibility from 16/24 to 22/24 runs. In a fixed-k=4 scaling study on a scaling probe of 4 to 12-qubits, the raw mask space grew from 495 to 12.1M while the evaluated masks increase only from 189 to 305. Resource-weight changes alter depth/routing priorities with at most a 0.44-point mean validation shift.

High-dimensional Vlasov equations present promising use cases for quantum simulation, but their transport coefficients must be implemented coherently in order to preserve a compact quantum representation. We develop explicit Schrödingerised circuits for prescribed external field Vlasov dynamics without classical field updates. In 1D1V, velocity-dependent streaming is compiled directly from the encoded velocity register, while a non-linear cubic field is evaluated using reversible fixed-point arithmetic. For fixed polynomial degree, the field workspace scales linearly with the coordinate register width, while the field evaluation subroutine has polynomial depth. As a proof of concept, we simulate a minimal coupled 3D3V anharmonic Penning system and realise mixed electric-field terms and transverse magnetic coupling on a six-dimensional phase space in agreement with classical calculations. Resource analysis shows approximately linear growth with the number of time steps, while identifying the auxiliary register as the dominant depth bottleneck. Structured preparation and register recovery of the auxiliary state reveal an interplay between loading cost and readout. Together, our algorithm demonstrates a fully coherent quantum simulation of high-dimensional Vlasov dynamics with variable coefficients and identifies the practical resource costs that must be controlled for large-scale quantum implementation.

We extend our previous study of squeezed two-component Schrödinger cat states to a phase-referenced single-mode family with an arbitrary number $N$ of coherent components and general relative phases. Within the established circular-state construction, we derive a closed complex overlap kernel for the ordered action of displacement, phase rotation, and squeezing, retaining exact finite-amplitude normalization. We distinguish finite-displacement orthogonality from local phase-estimation sensitivity quantified by quantum Fisher information (QFI). For equal-phase states, we compare $N=2,\ldots,9$ at a common mean photon number and include coherent-state and squeezed-vacuum benchmarks. A bound on the higher photon-number sectors establishes the fixed-energy asymptote $F_{Q,N}=4\bar n(N-\bar n)+o(1)$. Its leading term agrees with the known QFI of a vacuum--$N$-photon superposition. The resulting decrease of the ideal local quantum Cramér--Rao bound does not establish unlimited attainable precision: prior phase information, sample size, phase-reference resources, optical loss, state preparation, and measurement choice remain relevant.

Since the 1990s, experiments on double-well heterostructures have highlighted a key phenomenon: applying an external DC electric field induces pronounced wave packet oscillations at specific field strengths. \ To gain a deeper insight into this effect, a comprehensive quantitative analysis of the properties of quantum resonances near a crossing point is required. \ This approach lays the theoretical foundation for devising a quantum sensor capable of rapidly and efficiently determining whether the strength of an external DC electric field lies within a narrow target range.

Bell and contextuality scenarios are unified within the Acín-Fritz-Leverrier-Sainz hypergraph formalism, in which measurements are hyperedges. Multipartite measurements are obtained from product rules that combine independent contextuality scenarios into a single hypergraph. Several such rules exist: they are structurally distinct, yet yield the same classical, quantum, and boxworld correlations. Here, we show that this difference is not incidental, unveiling an unexpected connection. The measurements of composite Bell scenarios are exactly the process functions, the deterministic classical communication protocols that may be non-causal, i.e., lack a definite causal order without generating paradoxes. Validity of a hyperedge and logical consistency of a process function are thus one and the same condition. This allows us to characterize process functions by normalization and no-signaling alone, providing transformations that generate non-causal process functions from no-communication ones. The product rules, in turn, order process functions by causal structure, from no-communication to non-causality, which yields a graphical criterion for the latter: a process function is non-causal precisely when its hyperedge is generated by the disjunctive but not the maximal product. We thereby obtain the first joint hypergraph representation of (non-causal) process functions and (nonlocal-without-entanglement) measurements, recasting classical non-causality as a non-standard way of composing black boxes.

Based on the complex analysis theorem the principle of argument, a temperature-dependent formula for the Casimir-Lifshitz dispersion force of the interaction of two arbitrary plane-layered structures separated by either a vacuum gap of size d or a layer of size d consisting of an arbitrary dissipative dielectric with dispersion is derived. The formula consists of the temperature-dependent Lifshitz formula plus the temperature-dependent contour integral

Quantum computers require software to control the states of the qubits. As the actions on qubits grow in complexity with circuit execution, calibration, and benchmarking, the complexity of the control software grows in tandem. Spin-qubit quantum computers are at a stage where experimentalists need low-level access for tuning and calibration, and quantum algorithm researchers want high-level circuit-level access. In this article, we present the software design of SpinControl. SpinControl integrates three architectural metrics: 1) customizability, to allow prototyping devices and measurement protocols, is achieved by separating data and behaviour; 2) modularity and extensibility are achieved by separating functionalities into different components; and 3) robustness, to reliably execute quantum circuits on many qubits, is achieved by CI pipelines and input validation. SpinControl allows different types of measurements while customizing the instruments used, the pulse or circuit program executed, and the data processing. It allows building standardized experiments from measurement and analysis building blocks and executing these for calibration in a custom and conditional order. SpinControl implements these functionalities alongside robust configuration and data management, a connection to the cloud, and calibration scheduling. Pulse and circuit compilation, virtual gate matrices, as well as spin-qubit-specific GUIs integrated by SpinControl, make heavy use of software packages developed by Delft University of Technology: pulse lib, core-tools (both open source), and QConstruct

The Quantum Approximate Optimization Algorithm (QAOA) and its variants are leading algorithms to help solve challenging combinatorial optimization problems. QAOA maps these problems to Ising Hamiltonians such that their ground state is the desired solution. Candidate solutions are then drawn from a variational quantum circuit. The performance of QAOA hinges on a set of variational angles. However, finding good angles is an instance-specific and computationally expensive non-convex classical optimization task. Here, we learn the mapping from the problem instance to high-quality QAOA angles. Our learned models replace the per-instance optimization, that we call the solver, with a single forward pass that is several orders of magnitude faster than the solver with a near identical quality. Our models further generalize to unseen topologies such as Barabási-Albert and 2D grid graphs. Experiments on quantum hardware confirm that QAOA samples with angles produced by our open-source models are indistinguishable from solver angles. Crucially, models sensitive to the topology of the problem instance increase the quality of the QAOA angles. Our work amortizes a major bottleneck in QAOA by an up-front data generation and training cost. Importantly, this cost can be amortized over time in settings where many similar problems are optimized on a regular basis, as is often the case in applications for industry.

We establish an unconditional super-polynomial separation between quantum and classical PAC learning of Boolean functions under the uniform distribution in the large error regime. For every advantage $λ(n) = n^{-ω(1)}$, we construct a concept class that a polynomial-time quantum learner learns to agreement $1/2+λ(n)$ with success probability at least $1-1/n^k$. The learner uses only quantum random examples and outputs a polynomial-size deterministic classical circuit. In contrast, no polynomial-time classical learner achieves agreement $1/2 + λ(n)/n^k$ with success probability greater than $1/n^k$, even with membership queries. To achieve this, we develop a nearly-optimal quantum learner that uses quantum random examples to produce a hypothesis achieving a prescribed correlation with an arbitrary Boolean function. The learner generalizes Fourier sampling from parity hypotheses to quadratic hypotheses. While standard Fourier sampling is insensitive to the sign of the correlation, we use interference to bias sampling toward positively correlated hypotheses. This is combined with a careful analysis of the resulting distribution to boost both the learner's success probability and its agreement with the target function. We believe that the resulting quantum learning algorithm might be of independent interest. Finally, although a robust quantum PAC learning advantage holds unconditionally in the large error regime, we note that an analogous separation between quantum and classical learning in the small error regime would imply that $\mathsf{NP} \nsubseteq \mathsf{BPP}$.

We give an explicit construction of a pair of anticommuting Weyl displacement operators for a harmonic oscillator and use bounded functional calculus to obtain exact dichotomic representatives of the Pauli algebra. Two independent oscillators provide commuting Pauli algebras for Alice and Bob. The standard singlet-sector projector, written entirely in terms of these bounded oscillator observables, is then applied to the two-oscillator vacuum. We show explicitly that the projected vacuum has nonzero norm, so its normalization is well defined, has the exact singlet correlations, and reaches the Tsirelson value $2\sqrt2$ for the usual Bell--CHSH settings. We also clarify that the construction generally realizes a singlet sector with multiplicity, rather than selecting a unique vector in the full oscillator Hilbert space, and we compare the construction with the older pseudospin approach to continuous-variable Bell tests.

The exponential-SWAP (eSWAP) gate generates a coherent superposition of identity and SWAP operations, with continuously tunable amplitudes. We experimentally implement this gate between two bosonic motional modes of trapped ions using spin-independent and spin-dependent beam splitter interactions. Measurements of selected slices of the joint characteristic function for distinct input states test the gate and demonstrate continuous control of the identity-SWAP superposition. This implementation provides a tunable interaction for hybrid qubit-bosonic quantum information processing.

We theoretically study dc electric currents induced by rapid spin precession in noncentrosymmetric magnetic Weyl semimetals using the Floquet--Keldysh Green's-function formalism. The spin dynamics act as a time-dependent chiral gauge field and the geometric structure of electric currents is expressed in terms of the Berry curvature, the quantum metric, and the shift vector. For an isotropic Weyl cone, only an injection current is generated. This current scales quadratically with the driving frequency and linearly with the relaxation time associated with coupling to a fermionic bath. We further show that a finite Weyl-cone tilt modifies the available interband-transition phase space, smooths the frequency dependence of the current, and allows for a shift current and another type of injection current, both of which flow in directions determined by the tilt and the direction of the precession. A finite net current can remain after summing contributions from Weyl nodes of opposite chiralities when their transition phase spaces are inequivalent.

Control is a fundamental concept in quantum and reversible computational models. It enables the conditional application of a transformation to a system, depending on the state of another system. We introduce a general framework for diagrammatic reasoning featuring control as a constructor. To this end, we provide an elementary axiomatization of control functors, extending the standard formalism of PROPs to controlled PROPs. As an application, we show that controlled PROPs facilitate diagrammatic reasoning for quantum circuits. In particular, they admit a simple and complete axiomatization involving at most three qubits, whereas in the standard PROP setting, completeness necessarily requires axioms involving arbitrarily many qubits.

To solve linear systems $Ax=b$, we propose a sample-based quantum linear solver combining quantum Krylov-state sampling with classical variational diagonalization. Rather than simulating the cost Hamiltonian $H_b(A)=A^\dagger(I-|b\rangle\langle b|)A$, we measure quantum Krylov states $e^{-iAT}|b\rangle$ generated by the original Hermitian operator $A$ in the computational basis. We then classically diagonalize the projected cost Hamiltonian to reconstruct an approximate solution. Using a representation of $A^{-1}|b\rangle$ as a linear combination of quantum Krylov states, we derive lower bounds on computational-basis sampling probabilities from solution amplitudes. We establish support-discovery guarantees for finite nonnegative-time grid sampling and signed-time sampling, which permits both positive and negative evolution times. The former bounds the maximum evolution time, whereas the latter improves ideal shot complexity at the cost of occasional long evolutions. For a condition-number bound $κ$ on $A$, a lower bound $β_L$ on the solution probability weight of each of $L$ target basis states, and failure probability $δ$, signed-time sampling achieves $O(κ^2β_L^{-1}\log(L/δ))$ shots, matching a worst-case lower bound up to constants within an evolution-only observation model in a specified parameter regime. Finally, we analyze the effects of finite-length qDRIFT compilation and circuit reuse on sampling and derive an infidelity bound for the reconstructed solution.

Non-invertible symmetries extend conventional symmetries beyond group-like transformations and play an important role in quantum field theory and many-body physics. However, a general framework of non-invertible symmetries in open quantum systems is still lacking. Here, we formulate a general Liouville-space duality framework that extends Hilbert-space non-invertible dualities to open quantum systems. The resulting defect relates Liouvillians with dual Hamiltonian and dissipative parameters and becomes an exact symmetry at self-duality. We apply this framework to the periodic transverse-field Ising chain with two collective Lindblad channels exchanged by Kramers--Wannier (KW) duality. A strong $\mathbb{Z}_2$ symmetry divides Liouville space into four parity sectors, while the defect acts nontrivially only in the even-even sector. At self-duality, the KW defect imposes a momentum-resolved selection rule on Liouvillian Jordan blocks. Modes with different Liouville momenta or KW-defect eigenvalues cannot form a common exceptional Jordan block. For a three-site chain, a global Rényi-2 KW asymmetry dynamically identifies the self-dual conditions. At the same time, the spectral structure exhibits both a semisimple degeneracy and a self-dual exceptional point with a perturbation-selective response. These results extend non-invertible dualities to Markovian quantum dynamics and establish a symmetry-based selection rule for Liouvillian Jordan structures.

Predicting chemical reactions in biomolecules is challenging because reactive centers are embedded within complex environments that strongly influence their energetics and mechanisms. Here, we present a hybrid quantum-classical workflow that combines molecular dynamics, density functional theory, and correlated wavefunction methods, tightly integrating CPUs, GPUs, and quantum processing units (QPUs) to enable simulations across multiple length and accuracy scales. We apply this approach to ADGRG1 autoproteolysis, a maturation reaction in an adhesion G protein-coupled receptor that has not previously been studied using correlated electronic-structure methods. Our simulations treat a biologically realistic system containing more than one million atoms, including the full-length uncleaved receptor embedded in an endoplasmic-reticulum membrane, while incorporating a 54-qubit IQM quantum processor and up to 1,200 NVIDIA H100 GPUs. These results demonstrate how quantum computers can serve as accelerators within scalable scientific workflows, extending correlated electronic-structure methods to biologically relevant systems.

Photonic quantum technologies are based on controlled photon states. To generate these, quantum dots have emerged as excellent sources of single and entangled photons. In this Perspective, we briefly review the chronological development of quantum dots as photon sources, from their beginnings as quantum emitters in the early 2000s to the advanced photonic devices being developed today. We highlight the interplay between fundamental research and industrial aspects before discussing the photonic quantum technologies we expect to emerge in the near future.

We identify a class of nonintegrable quantum many-body systems composed of single Pauli strings that possess an extensive number of noncommuting local conserved quantities and exhibit partial ergodicity breaking due to exponentially degenerate energy spectra. We show that such systems exhibit a novel mechanism, Hilbert-subspace cloning, where the identical chaotic Hamiltonian acts on each of exponentially many disconnected Hilbert subspaces. Although the dynamics within each clone thermalizes, quantum coherence between clones remains protected and detectable by local observables. Consequently, the long-time behavior of local observables is described by a coherence-preserving partial Gibbs ensemble, where the hidden subsystem retains its initial quantum coherence.

We investigate dynamical quantum phase transitions (DQPTs) in the extended Agassi model following sudden quenches of same level pairing ($Σ$), monopole-monopole ($χ$) and cross level pairing ($Λ$) strengths. Using exact diagonalization, we characterize the non-equilibrium dynamics through the Loschmidt echo and intensive return-rate function. Quenches across equilibrium phase boundaries produce cusp-like structures in the return rate that shows non-analyticities with increasing system size. Equilibrium finite size to large scaling identifies the $χ$-driven transition as a second order phase transition similar to mean-field, Dicke, and Lipkin-Meshkov-Glick (LMG) models critical behaviour with the exponent of the order parameter $β\simeq 1/2$, while the $Σ$- and $Λ$-driven transitions are first order. We further characterize the associated dynamical singularities through a local scaling exponent $α$, with $α_χ\simeq 2/3$, $α_Λ\simeq 1/3$, and $α_Σ\simeq 3/2$ of all three parameters. The distinct scaling behaviours across the parameter channels show that dynamical criticality is not determined solely by the equilibrium order of the transition, revealing multiple dynamical scaling regimes. These non-analyticities are associated with the Fisher zeros of the Loschmidt amplitude, which cross the real time axis at critical times and the time derivatives of the return-rate function to characterize the order of DQPTs within the extended Agassi model.

Private simultaneous quantum messages (PSQM) provide a minimal model of noninteractive secure multiparty quantum computation, yet their communication complexity for concrete functions remains poorly understood. We show that familiar total functions already exhibit both genuine quantum advantages and strong structural limitations. For three-party equality on $n$-bit inputs, which determines whether the players' $n$-bit strings are identical, we construct an entanglement-assisted protocol with asymptotic communication $(1.633\ldots)n$ qubits, whereas every perfectly correct protocol without prior entanglement requires at least $3n$ qubits. For three-bit majority, one shared GHZ state and one transmitted qubit per player suffice for perfect correctness and perfect privacy, reducing the communication from the optimal classical cost of six bits to three qubits. Three-bit AND behaves differently. No perfectly correct and perfectly private protocol exists when the players share an arbitrary three-qubit state, apply arbitrary local unitary encodings, and transmit one qubit each. However, increasing the local dimension overcomes this obstruction: one shared three-qutrit GHZ state and one transmitted qutrit per player yield a one-shot protocol with total communication $3\log_2 3$. Together with the six-bit classical lower bound, this gives a strict quantum communication advantage. More generally, for every $k\geq 3$, we construct a perfectly correct and perfectly private one-shot protocol for $k$-bit AND using one qudit of dimension at most $k$ per player, and hence at most $k\log_2 k$ qubits in total.

We investigate the dynamics of coupled discrete time crystals (DTCs) in the coupled Dicke model or Dicke dimer (DD) with dissipation. By numerically simulating the mean-field dynamics of the system, we show that coupling two DTCs decreases their oscillation amplitude following a transient relaxation period. For sufficiently strong coupling, the coupled DTCs become unstable, resulting in the system relaxing towards the normal phase (NP). We demonstrate that the relaxation time diverges near the critical coupling strength, suggesting a continuous phase transition. Using the truncated Wigner approximation (TWA), we explore how the dynamics are affected by the introduction of quantum fluctuations. We also consider a scenario in which an NP is briefly coupled to a DTC, seeding the NP to transform into a DTC that is either synchronized or anti-synchronized relative to the DTC. We investigate the robustness of this phenomenon in the presence of noise. Using these results, we propose a scheme to perform NAND and NOR operations with three DTCs by sequentially coupling the input and output sites. We identify the parameter regimes in which the logic gate architecture remains valid, and investigate how the protocol is affected by the presence of quantum fluctuations.

Estimating statistical properties of probability distributions is a fundamental problem in statistics and theoretical computer science. We develop quantum algorithms for estimating the $q$-Tsallis entropy $\mathrm{H}_q^{\mathrm{Tsa}}(P) =\frac{\sum_{i=1}^n p_i^q-1}{1-q}$ when $0<q<1$, given purified quantum query access to a distribution $P$ on $[n]$. When $0<q\leq \frac{1}{2}$, we provide a quantum algorithm with query complexity $\widetilde{O}\rbra{\left(\frac{n}{\varepsilon}\right)^{\frac{1}{2q}}}$, which is optimal up to polylogarithmic factors. When $\frac{1}{2}<q<1$, we introduce a two-stage simultaneous probability estimation procedure, yielding a quantum algorithm with query complexity $\widetilde{O}\left(\frac{n^{\frac12+\frac{1}{2q}}}{\varepsilon^{\frac{1}{2q}}}+\frac{n^{1-q}}{\varepsilon}\right)$, which improves the result given by Chen et al. (ICALP 2026) when $\varepsilon=O\rbra{n^{1-2q}}$.

An encoding choice specifies the quantum error-correcting code used to encode logical qubits at a given node. Different encoding choices may differ in the number of physical qubits, the number of encoded logical qubits, the code distance, and the available fault-tolerant operations. We study different encodings for a distributed transversal fanout operation and look at its implications on node architecture. Our experiments suggest that an encoding with higher distance, even if requiring more ebits, can yield a lower logical error rate for distributed operations, and that ``upgrading'' an encoding prior to distributed operations and having a cache, as part of node architecture, for qubits can be useful for distributed operations.

We propose a hybrid quantum-classical framework for the unambiguous discrimination of pure states by combining the noisy intermediate-scale quantum semidefinite program solver (NSS) with the reciprocal-state representation. In NSS, a given semidefinite program (SDP) is represented within a subspace spanned by chosen ansatz states, with the required quantities estimated using quantum circuits, and the resulting optimization is performed classically. This makes NSS naturally applicable to discrimination problems involving circuit-prepared states, as finding a discrimination measurement can be formulated as an SDP. By choosing the discriminated states themselves as the ansatz and exploiting the reciprocal-state representation, the general matrix-variable NSS formulation is reduced to an optimization over N scalar variables, where N is the number of discriminated states. The resulting formulation reduces the number of optimization variables and positive-semidefinite constraints compared with the original NSS formulation. We further establish robustness guarantees against Gram matrix estimation errors, including a rescaling procedure that guarantees a valid positive operator-valued measure (POVM) under bounded perturbations. The resulting bounds quantify both the deviation in average success probability and violations of the no-error condition using only the estimated Gram matrix, its SDP solution, and a characterized perturbation bound, without access to the ideal Gram matrix. Numerical simulations validate the derived robustness bounds and characterize finite-shot scaling. We also perform experiments on IBM quantum hardware to estimate pairwise overlaps, and then evaluate the performance of the resulting POVMs.

Quantum processors are increasingly used as accelerators inside high-performance computing (HPC) workflows. A workflow runtime decides which quantum circuits to run, how to group them into provider jobs, and what to repeat after a failed attempt. Many search problems split into independent parts, but the runtime can use that structure only when the workflow exposes the parts and a validity check for each one. SemQBench measures what a runtime gains from this visibility. It compares seven execution policies for the same search problem, including two controls without amplitude amplification. The policies change one runtime choice at a time: whether to amplify, whether partial results may be combined across runs, whether the parts share one circuit, and what a retry keeps. We run them on the 20-qubit IQM Garnet processor using 106 distinct circuits in three jobs, and report circuit executions, active device time, and provider jobs separately before combining them in a cost model. Amplifying the problem as one whole circuit shows no statistically clear gain over random sampling and uses 6.7-104$\times$ more active device time. Exposing the parts and collecting valid partial results across a fixed batch of runs cuts the executions needed for 95% completion confidence by 2.20-4.00$\times$, and this policy is never worse than the other amplified policies in executions, device time, or jobs; it is selected in 99 of 108 overhead settings. Fewer executions do not always mean less device time: on one workload, executions fall from thirteen to four while active device time rises from 7.44 to 9.81 $μ$s. Exposing problem structure therefore gives the runtime a strong default policy and the measurements needed to decide when the simpler unamplified option is cheaper.

Two-stage stochastic combinatorial optimisation concerns discrete decisions made before all relevant information is known. An initial decision is made; once uncertainty is resolved, it can be adapted to the realised scenario, at a cost. The aim is to find the initial decision that minimises the upfront cost plus the expected cost of optimal adaptation. The first-stage decision problem is often NP-hard, and computing the expected minimum recourse cost can be $\#\mathrm{P}$-hard for a single first-stage candidate. We introduce Quantum Approximate Stochastic Combinatorial Optimisation (QASCO), a variational quantum-walk ansatz that coherently incorporates scenario-dependent recourse into its dynamics to search over first-stage decisions without explicitly evaluating expected minimum recourse costs. We demonstrate QASCO for MaxCut with stochastic edge weights, obtain a circuit with polynomial per-layer gate complexity, and study the ansatz via exact state-vector simulation. Across the instances considered, QASCO concentrates amplitude more effectively on stochastic-optimal first-stage decisions than a previously proposed two-stage QAOA construction. We further show that the ansatz can be calibrated using a depth-independent number of parameters and applied to unseen instances without further circuit-parameter optimisation, including joint decision--scenario--recourse spaces spanning more than $2^{32}$ configurations. Under a query-cost model, comparison with the tested classical heuristics using sample-average approximations of the expected minimum recourse cost shows that QASCO more reliably reaches globally optimal first-stage solutions while requiring fewer cut evaluations. These results show how to incorporate scenario-dependent recourse into the ansatz dynamics, providing a general framework for variational quantum walks in two-stage stochastic combinatorial optimisation.

Spin waves carry their propagation direction in the handedness of their circularly polarized stray field, a property inaccessible to scalar magnetometers. In the Damon-Eshbach surface wave of an in-plane magnetized film, the dipolar field above the film rotates with a handedness fixed by the direction of travel. The nitrogen-vacancy (NV) centre in diamond is an intrinsic polarization analyser: a right-handed field about the NV axis drives one spin transition, and a left-handed field drives the other, in both the ground and the excited state. Here, we exploit the two excited-state transitions, which lie inside the spin-wave band of yttrium iron garnet (YIG), as a pair of chirality channels and image Damon-Eshbach waves in both directions. Because reflection from an etched boundary reverses the handedness, the incident and reflected waves appear as two lines in one spectrum and are imaged separately. In the ground state, the same rule applies, and the selected field drives Rabi oscillations, a route to chirality-selective control of the NV spin by magnons. Reading the two channels gives the direction of a spin wave at one point, without a phase reference. This advances chirality-resolved quantum sensing and provides insight into chiral spin-wave dynamics.

The quantum foundations literature contains dozens of "no-signaling" arguments that rely on the Born rule or, more generally, the positive operator-valued measure (POVM) framework to show that the resources of non-relativistic quantum mechanics (NRQM) cannot be used to send superluminal signals. What these arguments typically establish, however, is not a prohibition on superluminal signaling per se, but the seemingly stronger claim that signaling at any speed between mutually isolated systems is forbidden. This paper gives a precise formulation of this claim, the no-signaling hypothesis, and investigates the following converse question: under what additional assumptions does it imply that all experimental outcome probabilities are described by POVMs? Surprisingly few are needed: given the standard NRQM representation of composite experiments and two textbook claims about marginal probabilities, the no-signaling hypothesis is equivalent to the universality of the POVM framework. More broadly, by formalizing the relevant concepts and deriving the logical relationships between them, the paper shows that the no-signaling hypothesis can be used to derive most, though not all, of the probability-generating fragment of NRQM. The resulting map of implications clarifies which common postulates of NRQM are logically interrelated and which can be modified independently.

Silicon nitride has emerged as a key material for the advancement of future quantum communication and computational devices. However, challenges persist in establishing a comprehensive development process, spanning from fabrication to optical characterization, essential for advancing these devices to their next stage of potential. Maintaining control over the entire process, from start to finish, alongside device modeling, enables more efficient and timely iteration and optimization. Here we introduce a fabrication-to-benchtop process. We employ an in-house stoichiometric recipe for device fabrication and conduct comprehensive characterization of optical losses and material properties. Understanding and controlling the refractive index of the device are vital for predicting device geometries and group indices. Implementing the refractive indices of our fabricated devices, we simulate microring resonators and demonstrate their application in generating optical solitons.

We investigate genuine multipartite entanglement and genuine tripartite nonlocality of a noisy generalized GHZ state in Schwarzschild-de Sitter spacetime. The genuine multipartite concurrence and optimized Svetlichny parameter are employed to characterize these two quantum correlations. It is shown that the black hole and cosmological event horizons redistribute genuine multipartite entanglement differently among the physically accessible and inaccessible reduced states, while Svetlichny violation occurs only in the physically accessible state. We find that genuine multipartite entanglement can survive in the physically inaccessible states even when genuine tripartite nonlocality is absent. In addition, initial white noise suppresses both correlations, with Svetlichny nonlocality surviving over a narrower parameter region. Furthermore, in the Nariai limit, under the normalization adopted here, the correlations become concentrated in the physically accessible state. These results demonstrate the different robustness of genuine multipartite entanglement and genuine tripartite nonlocality under horizon effects and initial noise.

Anderon, a quantum foundry operator, has released its first Superconducting Quantum Process Design Kit (PDK) for 300mm wafer fabrication. This PDK provides standardized design rules and building blocks for manufacturing superconducting quantum devices on their 300mm wafer line at the Albany NanoTech Complex. Anderon, backed by $2 billion in funding, offers various superconducting wafer types, including qubit, I/O signal, and amplifier/filter wafers. The post Anderon Releases First Superconducting Quantum PDK for 300mm Wafer Fabrication appeared first on Quantum Computing Report .

FirstQFM AB has achieved a 33% reduction in single-qubit gate execution times on QuantWare’s 21-qubit Contralto-D21 superconducting quantum processor, without compromising gate fidelity. This was accomplished using their patented quantum foundation model technology, which integrates with Quantum Machines’ OPX control hardware and QUA calibration stack. The model, developed with NVIDIA’s accelerated computing infrastructure, also improved two-qubit Bell-state fidelities. The post FirstQFM Foundation Model Cuts Quantum Gate Times by 33% on QuantWare QPU via NVIDIA Computing appeared first on Quantum Computing Report .

Insider Brief Sweden is joining European Skills Academies for Quantum and AI, with Nordita supporting the Nordic-Baltic Quantum Academy and Swedish organizations contributing to AI skills development. The European Quantum Skills Academy (EQA) brings together 73 partners and more than 100 affiliates across 23 countries, with a €19.8 million budget over 48 months and 50% direct EU funding. The AI Skills Academy initiative in Sweden will focus on AI education for sectors including healthcare and social care, with an emphasis on user participation, democratic principles and responsible technology use. Photo from Pexels by Efrem Efre . PRESS RELEASE &#8212; As quantum technologies transition from the laboratory to the market, the demand for a highly skilled workforce has never been greater. To meet this challenge, EQA has officially launched to establish a comprehensive, pan-European ecosystem for quantum education and training. Nordita, the Nordic Institute for Theoretical Physics in Stockholm, will play a key role in this initiative supporting the leadership of the Nordic-Baltic Quantum Academy — one of the EQA&#8217;s six regional quantum academies. Supported by a total budget of €19.8 million over 48 months (with 50% of it directly financed by the European Union) the EQA is the largest community in quantum workforce development to date. The project unites 73 partners and over 100 affiliates spanning 23 European countries. Aligning with the EU Quantum Europe Strategy, the EQA is designed to overcome fragmentation and ensure that quantum technology benefits all of Europe equally, thus fostering Europe&#8217;s technological sovereignty. These efforts align as well with the newly published Swedish strategy for quantum technology, in which Nordic Quantum — a network coordinated from Nordita — is highlighted as an example of collaboration in the Nordic region. The fact that Sweden via Nordita and Stockholm University enters the newly established European Skills Academy is

ORCA Computing has launched its PT-3 photonic quantum system in London, integrating it with NVIDIA GPU-accelerated computing infrastructure. This room-temperature system, consuming 6 kW, uses 64 photons across 128 qumodes to enhance classical machine learning models. The PT-3 is designed for generative AI in scientific research and large-scale industrial optimization, demonstrating improved protein designability and a 12x speedup in energy scheduling benchmarks. The post ORCA Computing Launches PT-3 Photonic Quantum System in London for Hybrid AI and Industrial Optimization appeared first on Quantum Computing Report .

Insider Brief D-Wave has delivered its Advantage2 annealing quantum computer to Villa Saporiti in Como, Lombardy, Italy, with installation planned to provide European researchers, universities and businesses with access to the system. Funded by Swiss Quantum Technology SA (SQT) under a €10 million agreement, the system, named VoltaB1 within the Q-Alliance ecosystem, will be accessible through D-Wave ’s Leap quantum cloud service once operational. The Advantage2 system features more than 4,400 qubits and is intended to support applications in optimization, materials simulation and other industrial workloads. PRESS RELEASE &#8212; D-Wave Quantum Inc. (NASDAQ: QBTS) (“ D-Wave ” or the “Company”), the only dual-platform quantum computing company providing annealing and gate-model systems, software and services, today announced at Digital Innovation Forum 2026 that its Advantage2 TM annealing quantum computer has arrived in Lombardy, Italy, for installation at Villa Saporiti in Como. Funded by Swiss Quantum Technology SA (“SQT”), the system, referred to within the Q-Alliance ecosystem as the VoltaB1, will give European researchers, universities and businesses access to powerful, production-grade annealing quantum computing technology once installed. Its arrival marks an important step in Q-Alliance’s work to turn Italy’s quantum ambitions into research capabilities, practical applications and industrial opportunity. The VoltaB1 Advantage2 annealing quantum computer will be formally inaugurated at Q-Alliance’s “ Quantum per l’Italia ” event on October 16, at the historic Villa Saporiti. Held as part of the lead-up to the bicentennial of Alessandro Volta’s death, D-Wave CEO Dr. Alan Baratz will deliver remarks during the special ceremony, which includes representatives from research, industry and government. The ceremony follows D-Wave’s momentous signing of the Volta Declaration at the World Tech Conference in Milan in June 2026, which established a framework for cooperat

Einstein's theory of general relativity describes gravity as the bending of spacetime, a mathematical model that combines three-dimensional space and time into a single, four-dimensional continuum. The theory also predicts that a rotating object, such as Earth, slightly drags the surrounding spacetime as it rotates, a phenomenon known as frame-dragging.

Insider Brief EMode Photonix raised $1 million in pre-seed funding led by Ground State Ventures , with participation from Harlow Capital Management, to expand its photonics simulation software business. The company says its software simulates nonlinear photonic circuits 1,000 times faster, helping engineers design devices for frequency conversion and quantum light generation. The Boulder-based startup will use the funding to expand product development and sales as it prepares an enterprise offering for complete photonic integrated circuit design. PRESS RELEASE &#8212; EMode Photonix ( EMode , Inc.), a startup delivering powerful simulation tools to allow novel photonics technologies for quantum computers to be developed faster, has raised a $1 million pre-seed round. The round was led by Ground State Ventures , with participation from Harlow Capital Management. Integrated photonics is one of the fastest growing and most exciting areas of technology currently. Traditionally developed for telecommunications, it is finding increasing use in sensing, computing (see Nvidia investing billions in partnerships with photonics companies to replace copper wire), and especially quantum technologies. Traditionally photonics engineers could rely on existing simulations of linear photonics, which is sufficient for simple light routing circuits. However, the next generation of photonic devices exploit non-linear photonics, which not only allows one to bridge and generate different frequencies of light, but even enables the conversion of classical to quantum light. Up until now, there haven’t been any efficient tools for simulating non-linear photonics. EMode Photonix has developed a unique simulation stack, based on proprietary computational techniques, that speeds up the simulation of non-linear photonic circuits by 1,000x. The technology has the greatest potential in the emerging field of quantum computing, explains CEO Eric Stanton: “Nearly every quantum computing platform relie

Insider Brief SEALSQ reported preliminary nine-month 2026 revenue of $16.3 million, up 65% year over year, and reaffirmed its full-year revenue guidance of $27 million to $36 million. The company reported approximately $463 million in cash, cash equivalents and restricted cash at September 30, 2026, alongside a management-estimated pipeline exceeding $200 million through 2029, including more than $100 million in post-quantum projects. SEALSQ said 42 prospective customers and partners were evaluating its QS7001 and QVault TPM products, with additional certification milestones and broader post-quantum revenue contributions expected in 2027 and beyond. PRESS RELEASE &#8212; SEALSQ Corp (NASDAQ: LAES) (&#8220;SEALSQ&#8221; or &#8220;Company&#8221;), a company that focuses on developing and selling Semiconductors, PKI, and Post-Quantum technology hardware and software products, today announced its preliminary unaudited financial metrics for the nine-month period ended September 30, 2026 (&#8220;9M 2026&#8221;), provided an update on operational milestones, and reaffirmed its full-year 2026 revenue guidance. 9M 2026 Key Financial Metrics Revenue growth of 65%: Preliminary unaudited 9M 2026 revenue of $16.3 million, compared to $9.9 million in 9M 2025. Strong liquidity: Cash, cash equivalents and restricted cash of approximately $463.0 million at September 30, 2026. Post-quantum pipeline above $100 million: An active, evolving business pipeline of more than $200 million through 2029 as of October 15, 2026, including more than $100 million associated with Post-Quantum projects, including the QS7001 and QVault TPM. These figures represent management estimates and are subject to risks such as conversion risk, customer validation, technical integration and other commercial risks. Revenue Drivers The 9M 2026 increase was driven primarily by: Continued strong demand for SEALSQ &#8216;s Vault-IC secure-element family across industrial, smart-energy IoT and P25 Radio protocol appl

Insider Brief SEALSQ and its subsidiary IC’Alps will showcase post-quantum security products and custom chip design services at electronica 2026 in Munich, Germany, from November 10–13. The company plans to demonstrate the VaultIC409 secure element, QVault TPM and QASIC custom ASIC design offer for integrating post-quantum cryptography into connected and embedded systems. SEALSQ will also present live demonstrations across several industries, including a TLS 1.3 demonstration of VaultIC409, while engineering samples of the secure element are planned for the second quarter of 2027. PRESS RELEASE &#8212; SEALSQ Corp (NASDAQ: LAES) (&#8220;SEALSQ&#8221; or &#8220;Company&#8221;), a company that focuses on developing and selling Semiconductors, PKI, and Post-Quantum technology hardware and software products, today announced its participation in electronica 2026 , November 10 &#8211; 13, 2026 at Trade Fair Center Messe Munich, Germany. SEALSQ, together with its subsidiary IC’Alps, will exhibit in Hall C6, Booth 670. Electronica is the world’s leading trade fair for the electronics industry. Held in Munich every two years since 1964, the last edition drew more than 3,480 exhibitors from 58 countries and over 80,000 visitors from 113 countries. It is where component makers, device manufacturers and system designers come to decide what goes into the next generation of connected products. SEALSQ will take part in the electronica conference program. On Wednesday, November 11, from 4:30 to 5:15 p.m., the Company joins NXP and Infineon for the roundtable “Physical AI at the Edge for Industrial Security” at the IIoT Forum . On Friday, November 13, at 11:50 a.m., SEALSQ will give a keynote at the Embedded Systems World Forum, “Embedding certified secure hardware to simplify migration to post-quantum security standards.” Live interactive demonstrations The booth will run live demonstrations across automotive, medical, smart energy, smart home and access-control applications, showi

Insider Brief Stony Brook University &#8216;s patented quantum memory technology, commercialized by Qunnect as Qu-MEM, has been named to TIME&#8217;s Best Inventions of 2026 list in the Experimental category. Qu-MEM is a room-temperature quantum memory designed to store and retrieve quantum information and operate with existing fiber-optic infrastructure for quantum networking. Developed from research led by Stony Brook physicist Eden Figueroa and his former graduate students, Qu-MEM systems are being deployed on quantum networking testbeds in New York and Europe. PRESS RELEASE &#8212; A quantum technology invented at the State University of New York (SUNY) at Stony Brook (Stony Brook University) is earning international recognition. Qunnect ’s Qu-MEM, a commercial room-temperature quantum memory device developed from Stony Brook-patented technology, has been named to TIME’s Best Inventions of 2026 in the Experimental category for concept inventions and prototypes showing future potential. This competition recognizes inventions that make the world better, smarter and more impactful. This recognition highlights Stony Brook’s role in advancing quantum technology and demonstrates how university research can move beyond the laboratory to help shape emerging industries. Qunnect ’s Qu-MEM grew out of research led by Professor Eden Figueroa, Stony Brook’s Endowed Presidential Professor of Physics and director of the Stony Brook University Quantum Institute alongside alumni/graduate students Mehdi Namazi, PhD ’18, and Mael Flament, MS ’19. Figueroa co-founded Qunnect with Namazi and Flament, who now serve as the company’s chief science officer and chief technology officer, respectively. Qu-MEM is the world’s first commercial room-temperature quantum memory device, currently expanding Stony Brook&#8217;s SCY-QNET, America&#8217;s largest quantum internet. It is an on-demand, warm-vapor, neutral-atom quantum memory that sits in a standard server rack. It is designed to work w

Insider Brief Leaders from nine blockchain organizations have launched the Quantum Alliance , an open standards initiative to define and verify post-quantum readiness across blockchain networks, wallets and infrastructure. The Alliance plans to publish open testing criteria, benchmarks and migration guidance covering transaction signatures, key management, consensus, zero-knowledge proofs and peer-to-peer connections. Its initial work will focus on four areas: blockchain migration, post-quantum zero-knowledge systems, wallet security and cross-chain compatibility. PRESS RELEASE &#8212; CEOs, CTOs, and founders from nine blockchain organizations today launched the Quantum Alliance , an open standards body that will set the criteria for judging quantum-resistance claims in blockchain and create standards for compatibility between the networks as they migrate. The Alliance will define what post-quantum readiness means for blockchain networks, wallets, and infrastructure, and how to test and verify any claim of quantum resistance.&nbsp; Nearly every major blockchain secures its accounts with elliptic-curve signatures, and once an account signs a transaction (for some address types, from the moment it is created), its public key sits permanently on a public ledger. A sufficiently capable quantum computer running Shor&#8217;s algorithm could work backward from that public key to the private key and take control of the funds.&nbsp; The same signatures protect stablecoin minting keys, governance contracts, bridges, and oracle feeds, so one compromised privileged key could spread across many platforms at once. Almost all of the roughly $2.9 trillion crypto market still relies on classical signatures, with 6.04 million BTC, 30.2% of supply, counted as quantum-exposed at rest. A growing body of forecasts places the first practical attack around 2028, and several of the most closely watched appeared within the past two years. Since early 2025, the Quantum Doom Clock , a model b

Researchers from Google Quantum AI, Google DeepMind, and MIT have developed a modular quantum error correction (QEC) architecture that significantly reduces the physical qubit overhead required for quantum computing. This new approach, detailed in a technical manuscript on arXiv, utilizes modular hyperbolic codes to achieve over 30x savings in qubit overhead compared to standard 2D surface codes. The architecture allows for high encoding rates without complex on-chip wiring, demonstrating high tolerance to noise in simulations. The post Google Quantum AI &#038; DeepMind Demonstrate Modular Hyperbolic Codes for Over 30x QEC Overhead Reduction appeared first on Quantum Computing Report .

Germany has released national guidelines for migrating to Post-Quantum Cryptography (PQC), aligning with the EU's roadmap. The strategy, driven by advancements in AI and threats to classical encryption, outlines a three-phase migration timeline, prioritizing high-risk systems by 2030 and aiming for full migration by 2035. This initiative mandates hybrid cryptographic mechanisms and PQC readiness in risk management for critical infrastructure. The post Germany Issues Joint Federal PQC Migration Guidelines to Align with EU Post-Quantum Roadmap appeared first on Quantum Computing Report .

IBM Research has developed an AI agent factory to automate the design of QEC decoder chips, achieving up to 204x hardware speedup and 11.5x lower AI inference costs. This system utilizes autonomous multi-agent search and open-weight models, making QEC chip design more economically practical for fault-tolerant quantum systems. The agent factory explores architectural transformations to optimize decoding algorithms for high-rate qLDPC codes. The post IBM Research Automates QEC Decoder Chip Design Using Open AI Agent Factories at 11.5x Lower Inference Cost appeared first on Quantum Computing Report .

When light hits a tiny defect embedded in a solid material like diamond or silicon carbide, it can kick the defect's electrons into an excited state. These spin defects have the potential to be used as stable, readable qubits for quantum technologies, for example, quantum sensing. But modeling the full physics of their energetics over time—a key step in developing spin defects into new technologies—is a challenging task.

Classiq has partnered with FreeYa Mind Campus to open a Quantum Applications Hub in Iași, Romania, which will serve as Classiq's regional headquarters. This hub integrates Classiq's quantum software platform with the campus's IBM Quantum System Two. The collaboration aims to drive quantum software development, education, and enterprise projects across Eastern Europe. The post Classiq Partners with FreeYa Mind Campus to Launch Quantum Applications Hub in Romania appeared first on Quantum Computing Report .

Insider Brief ZeroTier has released Release Candidate 3 (RC3) of ZeroTier Quantum, a networking platform designed to provide post-quantum cryptographic protection across managed, sovereign, self-hosted and air-gapped deployments. The release adds Windows, macOS, Linux and Android client support, credential-based device enrollment, controlled software delivery and administrative security event generation. ZeroTier says RC3 has undergone protocol and code audits and is being tested with customers, as the company moves toward production deployment using ML-KEM-1024, ML-DSA-87 and AES-256-GCM. PRESS RELEASE &#8212; ZeroTier , one of the world’s top software-defined networking companies, today announced Release Candidate 3 (RC3) of ZeroTier Quantum, the world’s only software-defined end-to-end quantum-secure networking platform. The release marks the final production step towards full deployment, proving ZeroTier Quantum can deliver secure, quantum-safe connectivity regardless of customer’s deployment type, location, or desired privacy posture. RC3 moves ZeroTier Quantum closer to production readiness through expanded flexibility, broader client support, stronger administrative controls, and continued testing and platform hardening. Organizations can deploy the platform as a managed service or in sovereign, self-hosted, and air-gapped environments. When it comes to defense, government, finance, critical infrastructure, and enterprise environments, flexibility means deploying quantum-secure networking in a way that fits existing architecture, security requirements, and operational needs, without a rip-and-replace approach. “For security-sensitive organizations, like government, defense, and critical infrastructure management, where a network runs matters just as much as how it’s secured,” said Andrew Gault, ZeroTier ’s CEO. “With RC3, we’re proving that quantum-secure connectivity can adapt to the environments organizations actually operate in. We have significant experie

Insider Brief ORCA Computing launched its PT-3 photonic quantum computer at Digital Realty’s London innovation lab, pairing it with NVIDIA accelerated computing for scientific AI and industrial optimization. ORCA reported that a PT-3-assisted version of NVIDIA’s Proteína model improved the proportion of useful protein designs by 20% compared with the classical baseline. ORCA said the PT-3 completed a hybrid energy-scheduling workflow in about an hour, more than 12 times faster than its predecessor at the same solution quality. PRESS RELEASE &#8212; ORCA Computing , the company pioneering quantum-accelerated AI for science, today launches the PT-3, the newest generation of its photonic quantum computers, and the first built to deliver commercial quantum advantage. The first system is live in the Digital Realty Innovation Lab (DRIL) in London, where it runs alongside NVIDIA accelerated computing.&nbsp; Quantum and AI for science AI for science, harnessing AI to transform scientific discovery, is rapidly emerging as one of the most important new categories in computing and a major industry-wide focus, yet it is held back by limited training data. ORCA’s PT-3 works alongside GPUs to increase the expressivity of AI models (their ability to represent complex patterns and data distributions), helping them learn more from limited data and identify better, more novel candidates for new drugs and materials.&nbsp; Already delivering results The PT-3 has allowed ORCA to generate results from a hybrid quantum-classical extension of NVIDIA Proteína , the generative model for protein design. Trained on 32 NVIDIA Hopper GPUs working with a PT-3 using 64 photons in 128 qumodes, the hybrid model showed enhanced designability over the classical baseline, improving the ratio of useful proteins by 20%, and generated novel proteins with a different mix of secondary structures. This builds on earlier life sciences results from ORCA’s PT-2 system. Working with the Technical University of D

Silicon spin qubits are a promising platform for building scalable quantum computers as they are compatible with the semiconductor manufacturing technologies used to produce today's computer chips. However, they have an important weakness: silicon spin qubits typically lose accuracy when several qubits are under parallel control. To be useful, quantum computers will need to operate many qubits simultaneously without compromising the accuracy of their operations.

By Zeynep Koruturk , Dr. Kris Naudts , and Donald Harmitt @ Firgun Ventures . Firgun Ventures is a VC firm investing in Series A/B quantum scale-ups globally. Demand for critical minerals is rising just as copper exploration is becoming harder. The IEA projects copper supply to fall around 25% short of primary requirements by 2035 , while the cobalt gap has widened to more than 25% following the DRC&#8217;s export quotas. Closing those gaps will require more primary supply, making new discoveries increasingly important. Yet many of the accessible targets have already been found, pushing exploration towards deeper, more complex targets. S&amp;P Global estimates that average copper drilling depth has risen nearly 50% since 2010 to around 600 metres, which means every unsuccessful deep target can require substantially more drilling before miners learn that the ore is not there. That cost is what makes measurement before drilling worth paying for, and two instruments are being built for the job. Quantum gravimeters use clouds of laser-cooled atoms as a stable reference for small variations in gravity caused by underground density differences, while quantum magnetometers read subtle magnetic field changes that reveal particular rock formations. Neither technology produces a complete underground map or removes the need to drill. What they offer is a better-calibrated sense of where to drill and, just as usefully, where not to. Better subsurface information informs which targets get funded, and underscores the question of who controls a country&#8217;s geological picture. And a useful by-product of deploying quantum technologies in the mineral sector is meeting the increasing material needs of quantum itself. What quantum sensors add to the mineral exploration toolkit Mineral exploration requires assembling an incomplete picture from indirect signals, among them sampling, seismic surveys, gravity and magnetic data, and the machine learning models built on them. A gravity a

Insider Brief Riverlane and NVIDIA are exploring how AI and GPU-accelerated computing can speed up decoder calibration for quantum error correction as quantum hardware behaviour changes. Using Riverlane ’s Local Clustering Decoder on an NVIDIA H100 GPU, the reported surface-code training cycle fell from three minutes on a single CPU core to 2.8 seconds. The H100 processed more than four million surface-code syndromes per second in the reported tests, compared with around 59,000 per second on a single CPU core, supporting more frequent decoder recalibration. PRESS RELEASE &#8212; Quantum computing has the potential to solve problems beyond the reach of today&#8217;s computers, from drug discovery to materials science and optimisation. But before that can happen, the industry must first overcome the errors that are created by quantum computing’s extreme sensitivity to noise.&nbsp;&nbsp; Quantum error correction (QEC) detects and corrects these errors. It’s essential for building reliable and useful quantum computers, but this also creates enormous demands for real-time data processing. Future systems may need to process terabytes of information every second, with near-perfect accuracy, to support error-free quantum computing.&nbsp; To explore how to meet these demands, Riverlane and NVIDIA are collaborating on the use of AI and NVIDIA accelerated computing for QEC, including how GPUs can make decoder calibration faster, and help quantum systems keep up with changes in hardware behaviour. Keeping up with Changing Quantum Hardware A decoder is the part of a QEC system that interprets the signals produced by a quantum processor. It works out which errors are most likely to have occurred and tells the system how to correct them. To do so accurately, the decoder needs a reliable picture of the errors that occur. It uses numerical settings, known as weights, to estimate how likely different types of errors are and decide which corrections to apply. These settings are based

Insider Brief Dirac Labs has joined the Wisconsin Security Research Consortium as an industry affiliate to advance GPS-independent quantum navigation for autonomous maritime missions. The Madison-based company is developing diamond-based magnetic sensors and AI processing to determine position underwater, underground and where GPS is disrupted or unavailable. The affiliation connects Dirac Labs with Wisconsin’s defense research network and supports Area 52, a proposed Lake Michigan testing ground for autonomous maritime systems. PRESS RELEASE &#8212; Dirac Labs, a Madison-based quantum-enabled navigation company, today announced that it has joined the Wisconsin Security Research Consortium (WSRC) as an industry affiliate, providing resilient navigation alternatives to enable autonomous maritime missions.&nbsp; WSRC, led by the Wisconsin Technology Council, connects Wisconsin’s universities, technology manufacturers and government partners to advance defense research and economic development opportunities in the state. Dirac Labs’ affiliation builds on the Autonomous Heartland effort to position Wisconsin — with its shipyards, airspace, industrial base, workforce, and research anchors — at the center of America’s autonomous and maritime future. Along with the Sagamore Institute, the Midwest Defense Accelerator and TitletownTech, WSRC supports the growing Area 52 initiative.&nbsp; Area 52 was originally proposed by retired U.S. Navy captain Jerry Hendrix to serve as the Navy’s equivalent to the Air Force’s Area 51. Hendrix argued that the Navy needed a secure area to develop and test autonomous and unmanned platforms away from the adversary surveillance possible in international waters. Lake Michigan is a uniquely suitable option, as it is the only Great Lake entirely within U.S. territory that is large and deep enough for both surface and subsurface testing, and it has existing FAA-designated restricted military airspace overhead connected to assets like Volk Field.&

Insider Brief FirstQFM applied its quantum foundation model to a 21-qubit QuantWare superconducting processor at the Israeli Quantum Computing Center, reducing single-qubit gate execution time by 33% without reducing gate fidelity. The model generated custom pulse-level gate implementations from existing calibration data and identified five qubit pairs with improved Bell-state fidelity, with the improvements confirmed in independent hardware runs. The work used Quantum Machines’ control and calibration infrastructure alongside NVIDIA accelerated computing, and FirstQFM plans to expand its optimizations as QuantWare develops larger quantum processors. PRESS RELEASE &#8212; FirstQFM today announced results from applying FirstQFM’s quantum foundation model to a QuantWare superconducting quantum processor at the Israeli Quantum Computing Center (IQCC). FirstQFM ’s foundation model builds on top of Quantum Machines’ native calibration stack, and generated single-qubit gates that reduced execution time by 33% on a QuantWare Contralto-D21 QPU. Gates were validated directly on the QuantWare processor using randomized benchmarking with no loss of gate fidelity. The model generated custom pulse-level implementations of gates from calibration data produced by the Quantum Machines’ calibration stack with no additional quantum hardware measurements required. This shifts more of the gate optimization process from scarce QPU time to classical compute. The model also identified improvements to two-qubit gates, which are central to entanglement and typically more challenging to calibrate than single-qubit operations. Using existing calibration data together with a short hardware probe, the model identified five qubit pairs with higher Bell-state fidelity with each improvement confirmed in independent hardware runs. The QuantWare processor was operated at the IQCC using Quantum Machines’ OPX control hardware, QUA software, and automated calibration infrastructure. FirstQFM developed

Insider Brief IonQ and the University of Cambridge have opened the IonQ Quantum Innovation Centre at the Ray Dolby Centre, establishing the company&#8217;s first university-based centre of this kind. The centre&#8217;s nine initial research projects will cover quantum networking, sensing, hardware development and applications in fields including chemistry, materials science, finance, engineering and medicine. IonQ plans to deploy a 256-qubit Superion quantum computer and an on-campus quantum network, while Innovate UK will provide the National Quantum Computing Centre with access and computing time over three years. PRESS RELEASE &#8212; IonQ (NYSE: IONQ), the world&#8217;s leading full-stack quantum platform and foundry, and the University of Cambridge have announced the opening of the first-ever university-based IonQ Quantum Innovation Centre. The Centre is located at the Ray Dolby Centre, the new home of the University&#8217;s Cavendish Laboratory. This initiative brings the University&#8217;s largest corporate research partnership from agreement to a physical home at one of the world&#8217;s leading facilities for physics research. The IonQ Quantum Innovation Centre demonstrates the company’s commitment to quantum innovation and academic research within the United Kingdom. Research at the Centre includes co-development of new quantum network nodes and sensing capabilities with the university, and a strengthening of the existing Cambridge-to-Bristol quantum network. IonQ and the University of Cambridge first announced the partnership on March 11, 2026, supporting advanced research and workforce development for quantum technologies. “The opening of the IonQ Quantum Innovation Centre turns a landmark agreement into a working home for quantum research inside one of the world’s most storied physics laboratories,” said Niccolo de Masi, Chairman and CEO of IonQ. “By bringing quantum computing, networking, sensing, and security research together at Cambridge, we are acc

We describe a practical approach for accessing the logical failure rates of quantum error-correcting (QEC) circuits under low physical (component) failure rate regimes. Standard Monte Carlo is often the de facto approach for studying the failure rates of quantum circuits. However, in the study of fault-tolerant error-correcting circuits, the ability to extend this approach to low physical failure rates is limited. In particular, the use of Monte Carlo to access circuits that are relatively large or have high correcting power becomes more difficult as we lower the input failure rates of the individual components (gates) in the circuit. For these reasons, many simulations studying the circuit model go no lower than end-to-end logical failure rates in the 10 &amp;#x2212; 6 regime.In this report, we outline an approach that borrows from earlier work by Bravyi and Vargo \cite{bv13} to the more complex circuit noise model. Earlier works studied both the capacity and phenomenological noise models \cite{bv13,Beverland2019,bonilla2021xzzx}, but the work is insufficient for generating similar simulations in the circuit-noise model. To the best of our knowledge, our team is the first to develop a full prescription of the rare event simulation by splitting technique for the circuit-based noise model. We have also generated promising results that are confirmed by standard Monte Carlo simulation under an accessible regime. This work shows that we can access noise in the circuit-model prescription of quantum error-correcting code to failure rates below 10 &amp;#x2212; 20 regime.

Abstract Variational quantum eigensolver (VQE) calculations are widely used as reference workflows for assessing near-term quantum hardware, but practical guidance on their accuracy, runtime, and billed usage remains limited. Here, we present a hardware-validated reference dataset for variational ground-state energy calculations of the hydrogen molecule H 2 on several IBM Quantum processors available in 2025–2026. Using a standardized Qiskit Nature workflow, we benchmark the impact of shot count, backend choice, fermion-to-qubit mapping, optimizer behavior, resilience level, and execution mode on the achievable energy accuracy relative to exact diagonalization. For the H 2 /STO–3G configurations examined, circuit simplification through tapered mappings provides the most consistent accuracy gains, resilience level 1 improves accuracy at a substantial billed-usage premium, and session-based execution yields no systematic accuracy advantage over single-job execution despite markedly higher billed time. The dataset and analysis provide a transparent baseline for assessing current IBM Quantum hardware for quantum-chemistry applications and for estimating the runtime effort and billed usage that non-specialist users can expect from standard workflows.

The unification of quantum theory and general relativity suggests the existence of a minimal measurable length, leading to a generalized uncertainty principle (GUP) and an energy-dependent vacuum group velocity. Testing these effects with macroscopic objects typically encounters the ``soccer-ball problem,'' where applying Planck-scale deformations to the total momentum predicts observationally ruled-out velocity deviations. We adopt the QFT-natural prescription in which the GUP modifies single-mode commutators, and verify by explicit calculation that the macroscopic group velocity of a multimode coherent pulse reduces to the single-photon GUP velocity evaluated at the central wavelength, multiplied by the classical Gaussian-beam factor, with no dependence on the total pulse energy. The energy--momentum relation $E=pc$ itself is unmodified; the deformation enters through the velocity--momentum relation and is equivalent to a modified dispersion relation in the wave vector, with a quadratic coefficient that depends on which of the two variables is used. The soccer-ball problem $\,$---$\,$ which arises only when the GUP is applied to the center-of-mass momentum of a composite system $\,$---$\,$ is therefore absent for coherent light, and macroscopic petawatt pulses probe the same parameter space as single high-energy photons. Building on this framework, we propose a two-color vacuum chronoscopy experiment using a short-pulse petawatt laser and its high-harmonic generation. By systematically varying the macroscopic beam waist, our setup separates Planck-scale kinematic shifts from classical diffraction delays, establishing a controlled, source-independent terrestrial methodology whose sensitivity we assess against current astrophysical bounds and against the dominant waist-independent systematics that limit it, residual-gas dispersion and the harmonic birth-time offset.

Implicit discretizations of transient heat conduction repeatedly generate sparse linear systems, making diffusion problems a natural test bed for quantum linear solvers. This study evaluates how accurately a variational quantum linear solver (VQLS) recovers the temperature field produced by one backward-Euler step of one-dimensional conduction on IBM quantum hardware. A pre-specified confirmatory experiment compares N=4 interior temperatures encoded on two qubits with N=8 temperatures encoded on three qubits using ten paired hardware blocks; a separately defined N=16, four-qubit extension is evaluated in five independently scheduled exploratory blocks. Local VQLS optimization reduces relative temperature-field error to approximately 10^{-8} for all three cases, establishing an essentially exact ideal reference at this scale. On hardware, mean relative L2 temperature-field error is 8.07% for N=4 and 20.14% for N=8, a paired increase of 12.06 percentage points (95% CI, 10.71-13.42; exact paired sign-flip p=0.001953). The exploratory N=16 mean is 24.75+/-1.84%. A pre-specified N=16 shot-count follow-up then evaluates the same locked circuit at 2,048, 8,192, and 32,768 shots in six independently scheduled blocks. Mean field error remains 23.64%, 24.57%, and 24.37%, respectively; the 32,768-minus-2,048-shot contrast is +0.74 percentage points (95% CI, -0.65 to 2.12; p=0.281). In contrast, ideal multinomial sampling predicts a reduction from 2.68% to 0.75%. Higher shot counts reduce block-to-block variability but do not recover the mean cold-side temperature field. The results show that full-field readout of a strongly nonuniform thermal state is limited by more than ordinary finite-shot sampling under the tested hardware conditions, motivating observable-focused quantum formulations for heat flux, stored energy, and selected temperatures.

Inflationary cosmology faces a fundamental gap between primordial quantum fluctuations and the classical cosmic history inferred from observations. Although the primordial quantum state is a superposition of field configurations, standard cosmology assumes one definite realization of curvature perturbations and uses classical perturbation theory to describe the resulting gravitational potentials, CMB anisotropies, and large-scale structure. Squeezing and decoherence of primordial fluctuations alone do not explain why this one-realization description is physically meaningful. We address this issue through Cosmological Classical Branches (CCBs), using the quantum-information-theoretic notion of physical records. In CCBs, distinct late-time matter components carry compatible records of the same primordial configuration. A record in one component makes that configuration readable, while a disjoint compatible record suppresses interference accessible to operations on the first. Each branch thus admits a common c-number primordial label at finite resolution, while the global quantum superposition persists. This Letter summarizes the framework developed in Ref.~\cite{Kuroda2026CCB}.

What separates quantum computation from classical computation when a classical model may retain every branch history and arbitrary causal memory? We study this question using history-resolved causal stochastic machines (HCSMs), which describe positive causal history laws. Probabilistic Turing machines (PTMs) embed in stochastic-ensemble models (SEnMs), which in turn embed in HCSMs. We prove that HCSM history laws coincide exactly with the fixed-basis, prefix-preserving diagonal sector of ideal quantum processes, denoted by $\mathsf{PTM}_{\rm proc}$ and distinguished here from algorithmic quantum Turing machines (QTMs). Coherent quantum processes extend strictly beyond this sector. The boundary is already visible in reversibility. Born-probability shadows of unitary gates preserve inverse composition exactly for basis permutations with phases. Outside this class, an exact positive stochastic simulation that supports universal quantum continuations must retain predictive information absent from visible probabilities. An inverse-recovery identity quantifies this phase ledger, and universal continuation forces the retained probability law to be tomographically sufficient for the quantum state. Under continuous full-state encoding assumptions, this requirement yields quantum-state dimension lower bounds. The familiar slogan $\mathsf{PTM}\subseteq\mathsf{QTM}$ is thereby sharpened into a precise classical boundary and a no-free-classicalization principle. Complete classical branching does not remove the predictive information needed to represent quantum coherence.

Programmable preparation of entangled quantum states is a central requirement for scalable quantum information processing, quantum networking and photonic quantum computing. Topological photonic platforms offer an attractive route towards robust quantum-state generation by encoding information in symmetry- protected optical modes, yet the generated entangled states are typically dictated by the lattice geometry and therefore lack programmability. Here we demonstrate programmable preparation of topological entangled states by inverse engineering the nonlinear optical pump profile of an integrated photonic lattice. Our approach enables deterministic control over both the dimensionality and modal structure of the generated entangled state while preserving its topological character. We experimentally realize silicon photonic topological superlattices in which the nonlinear generation pathway itself becomes programmable via tailored excitations. The superlattices host a multiband manifold of co localized topological interface modes, while coherently controlled inputs synthesize pump superpositions within this protected basis. We showcase this principle by selectively addressing topological biphoton eigenstates, steering correlations to produce a desired target state in a high-dimensional Hilbert space, and inverse-designing pump states that generate targeted Schmidt dimensionalities. Site-resolved two-photon correlation measurements remain reproducible across nominally identical fabricated devices, demonstrating robustness to realistic nanofabrication-induced disorder. Programmable preparation of topological entangled states establishes a pathway towards exploiting topological photonic modes as application-specific quantum resources, enabling tailored input states for high-dimensional quantum communication, quantum networking and photonic quantum computing.

By linearizing the hydrodynamic equations associated with the Madelung transformation in the context of Bohmian dynamics, we derive an effective metric for the phase perturbation around a background state. We show that the metric previously obtained previously by the same authors arises naturally as a particular case of a more general structure, in which the complete functional variation of the quantum potential is retained and external classical potentials can be incorporated. This generalization preserves the dependence of the quantum potential on the density and its spatial derivatives, generating additional terms that introduce dispersive corrections and act as sources in the effective Klein-Gordon equation. To organize these contributions, we introduce differential operators that separate the local sector responsible for the effective geometry from the corrections associated with the complete functional structure of the quantum potential. We identify the conditions under which these additional terms become negligible, recovering homogeneous propagation and the effective geometry for the Gaussian wave packet of a free particle.

The extrinsic information transfer (EXIT) and generalized EXIT (GEXIT) area theorems provide fundamental conservation laws that connect the rate of classical codes to the performance of maximum-a-posteriori decoding on binary memoryless channels. In this work, we generalize these area theorems to quantum error correction. We first develop a coset-entropy formalism for nested linear codes, where the message specifies a coset and encoder randomization selects a codeword within that coset. The area under the resulting coset (G)EXIT function equals the normalized dimension of the quotient. For stabilizer codes, the measured syndrome restricts the Pauli error but does not always determine its logical effect, and the remaining uncertainty is an entropy over logical correction classes. We show that this entropy equals a classical coset entropy associated with the stabilizer group and the Pauli operators that commute with it. The resulting quantum GEXIT function has area equal to the number of encoded qubits per channel use for any stabilizer code, and this applies to the depolarizing channel through its joint four-valued Pauli-error distribution. For CSS codes on the quantum erasure channel and under independent bit- and phase-flip noise, the logical correction problem separates into two binary coset-decoding problems. On the quantum erasure channel, the duality between the stabilizer group and the Pauli operators that commute with it gives a folding identity at complementary erasure probabilities. Using this and the area theorem, we derive an upper bound on the rate of code families with vanishing logical error probability that matches the capacity of the quantum erasure channel. For the depolarizing channel, we also derive a rate-dependent converse, using a connection between correction-class entropy and coherent information to establish an inequality involving the complementary channel.

Variational quantum algorithms have emerged as a promising approach for simulating open quantum systems, yet their expressive power and trainability remain poorly understood. We propose a variational framework for solving Lindblad master equations by minimizing a residual cost function using a compositional ansatz obtained by combining a classical neural network with a parameterized quantum circuit. The density matrix is represented through a purification on an enlarged Hilbert space, ensuring positivity, Hermiticity, and unit trace by construction, while all gradients are evaluated exactly via the parameter-shift rule. Beyond the algorithmic formulation, we derive an upper bound for the covering number of the proposed compositional model and compare it with that of purely quantum neural networks. Our analysis shows that the classical parametrization enlarges the effective hypothesis class while providing finer control over its complexity, thereby establishing a theoretical connection between expressivity, covering numbers, effective dimension, and the barren plateau phenomenon. Numerical experiments validate both the accuracy of the proposed method for representative Lindblad master equations and the theoretical predictions regarding gradient concentration. These results provide a unified variational and theoretical framework for the simulation of dissipative quantum dynamics using compositional quantum machine learning models.

The analysis of Hamiltonian Variational Ansätze centers on three fundamental questions: which states are exactly reachable from a given initial state, what native control depth suffices for local and global synthesis, and whether a bounded circuit extension can expose a direction of decreasing cost at a suboptimal output. We address these challenges by leveraging the dynamical Lie algebras (DLAs) associated with the circuits and the geometry of the initial state's orbit under the action of the corresponding dynamical Lie group $G$. We show that an initial state has a closed projective orbit whenever it is a nondegenerate eigenstate of a control Hamiltonian. Combined with asymptotic QAOA convergence, this guarantees exact, finite depth ground state preparation for architectures employing diagonal problem Hamiltonians and irreducible stoquastic mixers. We bound the number of native control exponentials required for local unitary synthesis and state preparation using DLA commutator filtration growth alongside reachable orbit dimensions. Complementing these local results, we construct global frameworks on invariant sectors equipped with full unitary or special unitary dynamical Lie algebras. These constructions yield explicit applications to Pauli-generated systems and constrained maximum independent set multi-angle QAOA circuits; specifically, we show that their native control costs are directly determined by commutator filtration depth and independent-set toggle-group geometry, respectively. Finally, if the dynamical Lie group is compact, the observable $H_P$ generates an admissible evolution ($iH_P \in \mathfrak{g}$, where $\mathfrak{g}$ is the DLA), and the projective orbit of the initial state contains a ground state ray of $H_P$, then a bounded depth, identity-initialized circuit extension exhibits either first-order descent or negative curvature at every suboptimal circuit output.

Fermi statistics suppress the elastic collisions that rethermalize a Fermi gas during evaporative cooling, creating a fundamental low-temperature bottleneck for producing quantum degenerate gases. We show that, for shielded single-component ultracold dipolar molecular Fermi gases in the Wigner threshold regime, this bottleneck is governed by universal threshold laws fixed by the effective dimensionality of the gas. In this regime, Fermi suppression of rethermalization scales quadratically with temperature in 3D but only linearly in 2D. Consequently, the thermalization-to-loss ratio is more favorable in 2D than in 3D, and these results suggest that 2D geometries are better suited for reaching deep degeneracy. We also present ab initio close-coupling calculations that agree well with experimental measurements on Fermi degenerate gases of KRb molecules, supporting our conclusions.

We describe the nanofabrication and loading of lithographically patterned, high aspect ratio $10$ $μ$m diameter silicon dioxide discs with thickness of $400$ nm into an optical standing wave trap in vacuum. We obtain motional spectra of the center of mass motion of the discs using a combination of interferometric and imaging methods. The method is capable of high-efficiency loading and optical trapping using small numbers of objects, of the order of a few particles, with customized geometries and sizes compatible with wafer scale nanofabrication methods. Disc-like particles in optical traps have been identified as promising candidates for detectors of high frequency gravitational waves or as sensitive accelerometers.

We show that the 2D classical spin model constructed in arXiv:2605.10943 hosts many metastable states at non-zero temperature which are stable to arbitrary Hamiltonian perturbations, providing the first such example. Our proof relies on a recursive application of the cluster expansion.

We study a Rydberg chain subjected to a two-tone periodic drive of the detuning $Δ(t)$ and Rabi frequency $Ω(t)$ at frequencies $ω_1$ and $ω_2=νω_1$ respectively with $ν\in \mathbf{Z}$. In the strong Rydberg blockade limit, such a system reduces to the PXP model and exhibits exact Floquet flat band. Here we determine, using a time-dependent Schrieffer-Wolff transformation, the domain of validity of such PXP dynamics once the blockade-violating processes are taken into account. We study the melting of such flat bands in the presence of strong, but finite, blockade strength. Using Floquet perturbation theory (FPT), we identify two mechanisms for such melting; the first occurs due to the presence of many-body resonances involving resonant production of nearest-neighbor Rydberg excitation pairs while the second involves virtual processes that access intermediate states with such pairs. Our analytical FPT results match with those obtained using exact diagonalization on a finite chain. We study the dynamics for $|{\rm vac}\rangle$ (Fock state with no Rydberg excitation), $|{\mathbb {Z}}_2\rangle$, and $|{\mathbb {Z}}_3\rangle$ (Fock states with Rydberg excitations on alternate and every third site respectively) initial states. We find that $|{\rm vac}\rangle$ shows exceptional stability against resonant pair formation while $|{\mathbb {Z}}_3\rangle$ exhibits flat band melting via virtual processes away from the direct resonances. We find oscillatory dynamics with large time period for the $|{\mathbb {Z}}_2\rangle$ initial state and the presence of Floquet scars that have large overlap with $|{\mathbb {Z}}_3\rangle$ state; these phenomena occur due to processes that are absent in the PXP limit. We propose measurement of nearest neighbor pair correlation functions using Rydberg atom quantum simulator platforms as an accessible experimental probe for these effects.

Heavy quarks are often treated as Brownian probes of the quark-gluon plasma. We formulate the irreversible entropy balance of their momentum distribution and separate the production generated by collisions from the driving caused by an evolving medium. For linear dynamics the production splits into two positive contributions, from directed momentum and from the momentum width. A static bath obeys an exact H-theorem. A cooling bath adds an explicit driving term, and longitudinal Bjorken expansion enters as a separate kinematic drive rather than as collisional production. For a Bjorken temperature protocol we derive closed-form strong- and weak-coupling limits of the total production. At strong coupling it exceeds the initial relative entropy by a term linear in the relaxation time, whose quasistatic part has the thermodynamic-length form. At weak coupling it vanishes inversely with the relaxation time. A positive strong-coupling slope therefore guarantees maximal dissipation at intermediate coupling. The same structure holds for a relativistic Fokker-Planck equation with a Jüttner stationary state, solved numerically for charm and bottom quarks under the temperature protocol. Linear-response coefficients computed from the static generator reproduce both limits, and the numerical entropy balance is satisfied to high accuracy.

Weak localization in two-dimensional disordered electron systems originates from constructive interference between time-reversed scattering paths, giving rise to a logarithmically divergent quantum-interference correction to the dc conductivity. This behavior is generally suppressed when time-reversal symmetry (TRS) is broken. In this study, using a band-projected framework motivated by spin- and valley-polarized rhombohedral $N$-layer graphene (RNG), we show that nonuniform quantum geometry can qualitatively modify quantum-interference corrections to dc transport. In particular, continuously tuning the quantum geometry can change the sign of the conductivity correction, corresponding to a crossover between localization and antilocalization tendencies. Remarkably, at special values of the parameter controlling the quantum geometry, weak-localization (WL) or weak-antilocalization (WAL) can re-emerge despite broken microscopic TRS. At these special points, the orbital structure of the Bloch states gives rise to an emergent antiunitary symmetry that protects a gapless Cooperon mode and restores the logarithmically divergent quantum-interference correction characteristic of WL or WAL. Our results establish nonuniform quantum geometry as a mechanism for controlling quantum interference and electron localization in multiorbital electronic systems.

Quantum states over time were introduced, in part, to extend Bayesian probability to quantum theory and have since found applications across diverse areas, ranging from quantum causality and open-system dynamics to tests of macroscopic realism. While axiomatic characterizations of these states exist for Markovian dynamics, a general framework accommodating non-Markovian dynamics is still lacking. Moreover, extending this framework beyond quantum mechanics to general physical theories also remains elusive. In this work, we develop an axiomatic framework for multi-time states within a class of operational probabilistic theories (OPTs) that includes quantum mechanics as a special case. Based on three assumptions---compositionality, reconstructibility, and spatio-temporal marginal consistency---the framework accommodates both Markovian and non-Markovian dynamics, and provides sufficient conditions to certify signaling and temporal memory within OPT. As a concrete application of our OPT framework, we fully characterize the unique multi-time state in boxworld and develop a method for Bayesian retrodiction of physical transformations there. Our general framework is consistent with quantum theory, reproducing several existing results. In the non-Markovian quantum dynamics, we establish a correspondence between multi-time states and the process-matrix framework, and fully characterize the multi-time states compatible with general dynamics. This correspondence also lets us infer quantum causal models from multi-time states, and as a proof of principle, we propose a semidefinite program to infer causal order from quantum multi-time states. These results provide a unified framework for studying spatio-temporal states, causal relations, and Bayesian reasoning within OPTs, with implications for both fundamental and applied research.

Direct continuous quantum phase transitions between phases that break distinct symmetries challenge the conventional Landau-Ginzburg-Wilson paradigm and provide a framework for deconfined quantum criticality. Here, we investigate a Landau-forbidden ferromagnetic-to-valence-bond-solid (FM-VBS) transition in a frustrated one-dimensional spin chain using superconducting quantum processors. Combining matrix-product-state-assisted circuit preparation with quantum-hardware measurements, we resolve the suppression of long-range ferromagnetic correlations and the redistribution of competing-order fluctuations across the transition. Distance-resolved correlations and finite-size analyses reveal signatures consistent with critical behavior. We further extend our investigation to nonequilibrium dynamics, directly preparing dimerized states and tracking the evolution of VBS order and joint FM-VBS fluctuations under local unitary interactions. Our results establish a versatile quantum-hardware framework for probing competing orders, critical correlations, and many-body dynamics beyond conventional Landau theory.

The non-stabilizerness, or "magic", of a quantum state is a common metric for the hardness of simulation on a classical computer, and is often quantified by the stabilizer Rényi entropy (SRE). We show how random superpositions of classically simulable states saturate the SRE to the symmetry-restricted Haar-random maximum. For any large-$N$ random pure-state ensemble satisfying the conditions of Schur's lemma, the average SRE of the $m$-component superposition $\langle M_2(m)\rangle=N-\log_2[\langle W(m)\rangle]$ is governed by an average witness $\langle W(m)\rangle$ that universally decomposes into a Haar floor and an ensemble-specific excess. As the number of components $m$ increases, the excess is suppressed, resulting in a logarithmic scaling of the SRE before plateauing at the Haar-valued maximum. We derive a general closed form for $\langle W(m)\rangle$ in the thermodynamic limit, and numerically verify our result for random stabilizer states and random Gaussian states.

I determine the leading finite-radius correction to the two-boundary response of a charged axion wormhole near its BPS endpoint. With $δ=a_*^2$, exact radial matching in a product axion--dilaton/saxion system gives a boundary eigenvalue that vanishes as $O(δ)$ and an off-diagonal Hessian entry of order $O(δ^2)$. Their combination produces a cross-boundary covariance linear in $δ$, with a negative first sub-leading correction on the branch studied here. I determine the semiclassical range in which the quadratic approximation remains controlled and identify the first finite-radius angular resonance, $δ^2\log(δ/δ_0)$. Under a uniform rescaling of all active charges, the coefficient of the linear cross-boundary response scales as the inverse square of the charge scale. I then average the inverse response over the chiral Gaussian ensemble describing the BPS endpoint. Boundary reduction preserves the hard-edge index. Multiplication by the matched BPS sector weight converts the normalized response into the leading finite-radius two-source coefficient.

Significant efforts are currently being directed toward the implementation of large-scale quantum information processors, but realizing useful quantum advantage also requires the development of efficient quantum algorithms. While for many practical problems the dominant resource costs are associated with a small set of computational primitives, optimizing them in the quantum setting presents unique challenges, including a reversibility constraint absent from ordinary classical computation. Here we introduce an evolutionary framework in which large language models (LLMs) propose circuit designs and an independent evaluator verifies and scores them. We apply this framework to tasks spanning numerical computation, chemistry, optimization, quantum simulation, and number theory. In seven of the eight tasks, the discovered circuits significantly reduce both Toffoli and qubit counts relative to the state of the art. In the eighth, the search discovers a new reversible architecture for prime-field modular inversion. By handling reversibility differently, the architecture makes divsteps -- a classical algorithm previously impractical for reversible integer arithmetic -- viable and substantially improves the Toffoli-qubit trade-off for modular inversion. These results open the door for evaluator-guided LLM co-design of new algorithmic structures for quantum computation.

Quantum low-density parity-check (qLDPC) codes have a canonical mixed state---the normalized projector onto the code space---that lies at the intersection of quantum error correction and quantum many-body physics, yet the stability of its information-theoretic structure under local noise remains poorly understood. Recent progress on mixed-state phases of matter has identified the spatial decay of conditional mutual information (CMI) $I(A:C|B)$ as a key diagnostic of such stability, analogous to the role of the spectral gap for quantum ground states. We prove that, for the normalized code-projector state of a $\mathbb{Z}_d$ qLDPC stabilizer code under local Pauli noise, the CMI across a buffer $B$ separating $A$ from $C$ decays exponentially with the width of $B$ in two complementary noise regimes independent of system size. At weak noise, this holds for full-system tripartitions, where correlations between the two sides require an error cluster to cross the buffer, an exponentially unlikely event. At strong noise, exponential decay holds whenever the buffer supports no logical operator, since correlations can persist only along rare chains of buffer qudits that remain informative. Under an additional space-uniformity assumption, we establish the robustness of Levin--Wen topological entropy. On finite-dimensional lattices of size $n$, the weak-noise bound further implies a constant-layer quasi-local Petz recovery channel of range $O(\poly(\log n)/\varepsilon)$ that recovers the noiseless state within trace-distance error $\varepsilon$. Both CMI bounds apply to general qLDPC interaction graphs, including geometries where such constant-depth quasi-local recovery need not exist. Thus, the exponential decay of the noise-induced CMI provides a general criterion for mixed-state phase stability.

Motivated by recent experimental signatures of fractional Chern insulators in 2D quantum materials, we investigate the realization of $\mathbb Z_3$ parafermion zero modes (PZMs) on edges of spin-polarized $ν=2/3$ fractional quantum Hall states which are proximitized by superconductors. Unlike the spin-unpolarized Halperin state, the polarized $ν=2/3$ edge contains counterpropagating electron and fractional quasihole modes, giving rise to a plethora of competing tunneling and pairing processes. We focus on the vicinity of the fixed point where these modes reorganize into decoupled charge and neutral sectors, with the neutral sector describing an emergent dipole degree of freedom. Using bosonization and renormalization group analysis, we lay out the parameter space in which the interedge dipole interactions gap the neutral sector to stabilize one dominant tunneling and one dominant pairing channel resulting in a double sine-Gordon model in the charge sector which supports $\mathbb{Z}_3$ PZMs at domain walls. We discuss both clean and disordered systems. In clean systems this mechanism requires a certain degree of control of the interaction strength and range. In contrast, disorder can provide a more generic route: While short-ranged, edge-uncorrelated disorder % on the two edges suppresses the simultaneous pinning required for stable parafermion modes, when the disorder on the two edges is sufficiently correlated, as expected for smooth disorder potentials, the parameter regime hosting PZMs increases.

The quantum-trajectory description of a noisy quantum circuit is not unique: every Kraus representation of the noise channel defines a different unraveling, i.e., a different ensemble of pure states that averages to the same density matrix. While all unravelings share the same expectation values of observables, they generally differ in the amount of quantum resources carried by the individual trajectories. Here we study non-stabilizerness, or magic, quantified by the stabilizer Rényi entropy, in quantum-trajectory unravelings of Haar-random and $T$-doped random Clifford brickwork circuits subject to local dephasing noise of strength $p$. The canonical unraveling in terms of Pauli jumps is Clifford and leaves magic untouched, so that trajectories retain the Haar-random value of non-stabilizerness. Exploring the full two-parameter family of minimal unravelings, we find that the trajectory-averaged magic can be substantially reduced by a state-independent choice of Kraus operators, and that the optimal choice is not in general the projective-measurement unraveling, but a two-outcome generalized measurement in which the Kraus operators correspond to a weak measurement of the noisy qubit. The optimal unraveling reduces the extensive magic density of the trajectories by a $p$-dependent factor without altering its linear scaling with system size. At the same time, it produces a very broad distribution of magic over trajectories, with a sizable fraction of trajectories retaining Haar-random magic. Since the cost of stabilizer-based classical simulation grows exponentially with the magic of the state, these high-magic trajectories, rather than the average, control the simulation cost. Our results delineate the potential and the limitations of unraveling optimization as a route to the classical simulation of noisy quantum dynamics with stabilizer methods.

Classical simulation of magic state factories, including distillation, cultivation, and code switching, is challenging because of their substantial non-Clifford content. We introduce $\texttt{magna}$ (magic-state-factory assessment via global network algebra), a classical simulator that simulates such protocols as cheaply as Clifford circuits. $\texttt{magna}$ expresses the figures of merit of a protocol, namely the acceptance rate and the fidelity of the accepted states, as tensor networks, which it reduces globally by exploiting a structural correspondence with transversal gates on quantum codes. $\texttt{magna}$ further supports feedforward conditioned on arbitrary functions of mid-circuit measurement outcomes, including decoder outputs. We simulate Bravyi--Haah distillation with up to 100 output magic states at a cost that does not grow exponentially in the number of outputs, and achieve state-of-the-art sampling times for distance-5 magic state cultivation on both color codes and RP$^2$ surface codes. Finally, we validate nonlinear feedforward on a logical-level distillation protocol with 15 rounds of decoder-dependent feedforward. $\texttt{magna}$ aims to contribute to the key infrastructure for the large-scale evaluation and optimization of magic state factories.

The classical capacity of a noisy optical channel is the maximum rate at which information can be transmitted reliably, given a constraint on the mean input energy. For the ubiquitous bosonic Gaussian channels, which include standard models of loss and noise in fibre and free-space optical links, determining this rate requires addressing whether entanglement between channel uses or non-Gaussian signals can outperform Gaussian encodings. More precisely, the question is whether the energy-constrained Holevo information is additive across arbitrarily many channel uses and coincides with its Gaussian counterpart. We answer these fundamental questions in the affirmative for every single-mode bosonic Gaussian channel at every input energy. Namely, we prove that independently prepared Gaussian states with Gaussian-distributed random displacements achieve the capacity, including in the low-energy regime where squeezing the signals competes with encoding information in their displacement. Our proof connects an entanglement inequality to a sharp, additive lower bound on output entropy. We then characterise communication above capacity: under a strict total photon-number cutoff, the probability of correct decoding decreases exponentially with the number of channel uses, and we derive explicit bounds on the decay exponent. When only the mean photon number is constrained, a simple energy-rescaling formula determines exactly the entire asymptotic rate--error trade-off: the capacity at mean photon number $N$ and allowed average decoding error $ε$ equals the vanishing-error capacity at mean photon number $N/(1-ε)$. Together, these results identify the ultimate limits of classical communication for some of the most fundamental models of optical communication.

Moiré semiconductors provide a physical realization of the Hubbard model. Bandwidth-tuned Mott transitions and complex phase diagrams mimicking those of high-temperature superconductors have been demonstrated near a weak Mott insulating state at half-band-filling. The platform also provides an opportunity to explore the physics of a partially filled Hubbard band at doping densities far away from the Mott insulator, a regime that has remained largely unexplored. Here we report the emergence of an extended strange metal (ESM), in both doping density and twist angle, in a partially filled Hubbard band of twisted bilayer WSe2. The ESM is in the clean limit, persists down to 100mK, and spans over multiple symmetry-breaking ground states; it also appears only at small twist angles, where electronic correlations are strong. These observations distinguish the state from the reported strange metals associated with quantum criticality and favor the viewpoint that it is an intrinsic state of matter. We also report the observation of a new superconducting dome being developed from the ESM but far away from both the Mott insulating state and the van Hove singularity of the material. Our work opens the door to exploring the new regime of partially filled Hubbard bands in the clean limit.

Capturing static and dynamic electron correlation simultaneously at manageable computational cost remains a key challenge in electronic structure theory. Motivated by the recurring role of effective temperature in self-consistent field methods we extend the adiabatic connection mechanism from density functional theory to include a temperature dimension. This gives rise to thermally enhanced hybrid functionals, in which static correlation is captured via fractional occupations generated by an effective "correlation temperature" within thermal Hartree-Fock, while dynamic correlation is described by established density functional approximations. The framework formally unifies information-density matrix functional theory (i-DMFT) and thermally-assisted-occupation (TAO-)DFT as special cases, clarifying their theoretical basis and the respective prescriptions for the temperature parameter. We assess the performance of several thermally enhanced hybrids for different cases where i-DMFT was previously shown to fail. Furthermore, we discuss and test different schemes for determining the correlation temperature and investigate the accuracy of different such choices for a benchmark set derived from biphenyl. The results help to clarify the achievable balance of accuracy, generality, and efficiency, establishing thermally enhanced hybrids as a systematic route toward low-cost treatment of both correlation types.

Fault-tolerant quantum computing (FTQC) introduces substantial systems-level complexity through quantum error correction (QEC), making debugging FTQC programs challenging. Existing quantum debugging approaches primarily target logical-level circuits and do not naturally support debugging within realistic FTQC execution flows. We present SynDebug, the first systems-level debugging framework for FTQC programs. SynDebug introduces lightweight assertion-based debugging primitives that operate directly within encoded FTQC infrastructures while avoiding additional logical surface area and minimizing temporal overhead. We evaluate SynDebug across multiple QEC code families, code distances, and encoded workloads, including state preparation, entanglement validation, and Shor-style programs. Our results demonstrate that SynDebug enables practical FTQC debugging with an average 1.8% additional circuit depth overhead (0% in most cases) and no measurable increase in the logical error rate, showing that systems-level debugging for large-scale FTQC applications is both feasible and practical.

We investigate the fate of quantum many-body scars in the PXP model subject to Markovian dissipation. We show that when local jump operators respect the same symmetries of the Hamiltonian the full Liouvillian spectrum displays a tower of states with properties analogous to standard quantum scars: large overlaps with Néel states and equally spaced gaps in the imaginary part of the eigenvalues, set by a single frequency. Whether the long-time dynamics is dominated by scars is determined by the real parts of the eigenvalues, which are set by the ratio between the two relaxation rates $γ_{\pm}$ describing spin flips down-to-up or up-to-down respectively. For asymmetric dissipation ($γ_+ > γ_-$) the scarred eigenvalues have the smallest real parts: the resulting enhanced fidelity oscillations are further stabilized by staggered jump operators. In contrast, replacing the full projection operator in the dissipators with a partial one breaks the symmetries of the problem and is seen to destroy dissipative scars altogether.

Fault tolerant quantum computers greatly benefit from having both high fidelity entangling gates and a non-local qubit connectivity. However, most entangling gates for neutral atoms are local, requiring separated atoms to be moved using optical tweezers to yield entanglement between them. Here, we design a high fidelity Mølmer Sørensen-like entangling gate between neutral atoms coupled to a photonic cavity, enabling a programmable all-to-all connectivity through the shared cavity coupling. The gate is both robust to changes in cavity photon number, and enables selective entanglement between any subset of separated atoms through local laser addressing. This eliminates the need to physically move atoms to perform the gate, and therefore motional errors and erasure are suppressed. Using experimentally realistic parameters we demonstrate gate fidelities exceeding $F > 0.99$, with higher fidelities achievable through optimal control of the pump amplitudes.

We develop a technique to perform efficient unitary time evolution of a general spin Hamiltonian based on the system with identical qubits, as naturally realized by permutation symmetric atomic ensembles. We employ Cartan decomposition method to the associated Hamiltonian Lie algebra and construct the symmetry adapted generators to implement unitary operator of the ensemble Hamiltonian. This enables the compact circuit representations of the system dynamics in terms of experimentally accessible collective spin operations and exploits the Dicke basis structure of the ensembles as an effective qudit representation. We benchmark Cartan based evolution against both exact time evolution and the Suzuki Trotter product formula. Our results show that the Cartan protocol accurately reproduces the operator dynamics, spin expectation values, and fluctuation observables with zero error that are substantially smaller than those obtained through Trotterization while maintaining an optimized circuit structure. In addition, scaling analysis with the ensemble size demonstrates that the Cartan error remains independent of the atom number while the corresponding Trotter error increases with the system size, highlighting the improved efficiency of the Cartan approach for a larger system size.

The paradigm of a simple unstable theory in the sense of Shelah is the theory of the random graph, the Fraïssé limit of the finite graphs. Quantum error correction has a paradigm of its own, and we show that it is the counterpart of the random graph: the Pauli group on countably many qubits, taken modulo phases and with commutation as its relation, is the Fraïssé limit of the finite alternating spaces over the two-element field, and its form computes the syndromes of stabilizer codes. Seen through this correspondence, simplicity theory turns out to be a theory of error correction. Clifford encoding circuits implement the homogeneity of the Pauli group, forking recognizes the logical errors, and the independence theorem of Kim and Pillay is the gluing of syndromes. The two paradigms look alike as first-order structures, and they part company only when observables enter. Each defines a bipartite observable, and we prove that, once preparations are mixed, both acquire the tree property of the second kind in real-valued logic. They reach it by different roads, however, and we show that the probes decide which. The probes of the Pauli observable are the Pauli channels; for them the indicator of each syndrome sector is the difference of the responses of two uniform mixtures, and actual mixtures already witness the tree. The probes of the Rado observable see only marginals; conditions given by actual mixtures remain compatible on disjoint blocks, and the tree must be sought among idealized preparations.

Semiconductor spin qubits offer a promising route to compact and scalable quantum computers, combining long coherence times in isotopically purified silicon with compatibility with semiconductor manufacturing. Beyond computational speedup, their energy efficiency is an important consideration for future large-scale systems. We evaluate the power and energy requirements of a Loss-DiVincenzo spin-qubit quantum computer by analyzing the Quantum Fourier Transform (QFT) and benchmarking it against the classical Fast Fourier Transform (FFT). We develop a detailed energy budget, identifying cryogenic cooling as the dominant baseline contribution before quantum error correction (QEC). The comparison between the QFT and the classical FFT reveals that, for any quantum workload operating under a polynomially bounded sampling regime, the crossover in energy consumption occurs at smaller problem sizes than the crossover in execution time. Thus, quantum computing can become energetically competitive before achieving a speedup in execution time. We then incorporate surface-code QEC and analyze the energy costs of QEC cycles, gate synthesis, and decoding. At scale, instrumentation and decoding become dominant contributions, while cryogenic cooling imposes a constraint on scalability. We show that optimizing the control-signal demultiplexing ratio can reduce the overall energy cost by approximately two orders of magnitude. For a system with about one million physical qubits, we estimate a power consumption of approximately 100 kW, at least one order of magnitude below that of today's highest-performance classical computing systems.

Greenberger-Horne-Zeilinger (GHZ) states are multipartite entangled quantum states that play a central role in quantum information theory, with applications in quantum communication, cryptography, and distributed quantum computing. A major experimental goal is to create high-dimensional GHZ states using multiple entangled parties. Krenn, Gu and Zeilinger discovered a surprising bridge between these quantum-optical experiments and graph theory: certain photonic experiments can be represented by edge-coloured, edge-weighted graphs, and the dimension of the produced GHZ state equals the number of feasible monochromatic inherited vertex colourings. This led Krenn and Gu to conjecture that every GHZ graph with more than four vertices has dimension at most $2$. A counterexample would give a new high-dimensional multipartite GHZ construction, while a proof would clarify fundamental resource limitations in quantum optics. It is known that the conjecture holds for graphs of vertex connectivity at most $2$ [MFCS 2024], and that simple GHZ graphs with $n>4$ vertices have dimension less than $n/\sqrt{2}$ [Quantum 2024]. However, no general upper bound depending only on vertex connectivity was known. We prove that every simple connected GHZ graph $G$ with at least four vertices has dimension at most $2^{κ(G)-1}+\binom{κ(G)}{2}$, where $κ(G)$ is the vertex connectivity of $G$. We also prove new bounds in terms of edge connectivity and maximum degree.

Assuming only the solubility of Kirchhoff's laws, the conservation of energy, and the form of the constitutive relations, we present a flux-charge symmetric Hamiltonian formalism that always admits a symplectic reduction for nonsingular, well-posed circuits involving gyrators, inductors, and capacitors (LCG circuits) with arbitrary non-linearity. The formalism introduces a notion of circuit duality on non-linear non-reciprocal circuits and a family of point transformations that inserts, removes, and moves reciprocal elements across gyrators while preserving the Hamiltonian spectrum. With these transformations, we extend Tellegen's classic result that gyrators make reciprocal elements behave as their dual to non-linear reciprocal elements such as the Josephson junction and quantum phase slip. Furthermore, we present conditions under which non-reciprocal circuits can be transformed to dynamically equivalent reciprocal circuits.

It is common wisdom that a better understanding of how to quantify electron correlation should lead to more efficient treatments of the correlation problem. Here, we not only substantiate this view but turn it into a concrete, systematic framework for ground states. Since prominent correlation measures such as the nonfreeness depend only on the one-particle reduced density matrix, modeling the correlation energy as a function of such a measure naturally places the framework within reduced density matrix functional theory, while keeping the cost at mean-field level. Strikingly, the variable conjugate to the measure emerges as a ``correlation temperature'', thereby connecting correlation measures, functional theory, and effective temperatures. The framework rationalizes methods such as i-DMFT, and we illustrate its key concepts analytically for the Hubbard dimer and numerically for small molecular systems. This brings a fundamental question within reach: how much of the correlation problem can be solved at mean-field cost?

We introduce patchwork, a lattice-surgery compiler for arbitrary multi-qubit Pauli measurements on a prescribed narrow-corridor two-dimensional surface-code layout. Systematic geometric rules simplify stabilizer placement and gate scheduling, including for logical $Y$ measurements implemented using twist defects. We introduce measurement circuits and schedules that, together with protruding lobes of $Y$-extension patches, preserve the full effective code distance for all numerically tested code distances. To support parallel decoding, we develop a wavefront algorithm that partitions merged lattice-surgery patches into space-time commit, buffer, and cleanup regions. Simulations of three sequential multi-qubit Pauli measurements acting on ten logical qubits show that staged decoding achieves total failure probabilities close to those of monolithic decoding over the parameters tested. These methods provide an automated framework for fault-tolerant lattice surgery and a route toward scalable, real-time decoding.

Tests of gravity-mediated entanglement aim to determine whether two massive objects in spatial superposition can become entangled through their mutual gravitational interaction. In an ideal model, the two objects are often treated as pointlike branches, but real wave packets have a finite width and are also exposed to dephasing and residual non-gravitational forces. We study these effects in a two-branch gravitational cat-state model with Gaussian wave packets. The Newtonian interaction is averaged over the finite wave-packet width, and spatially correlated dephasing is included phenomenologically. We then ask a practical question: when does the generated state remain useful rather than merely entangled? To answer this, we examine Bell violation, teleportation fidelity, coherent information, Fisher information, and state distinguishability. We find finite parameter windows where the same state is Bell-nonlocal and teleportation-useful, but these windows shrink as the wave packets become broader or the dephasing becomes stronger. We also show that a residual electrostatic branch interaction can coherently cancel the gravitational nonlocal phase and strongly suppress the operational signal. The results identify finite-width and electrostatic tolerance boundaries that should be considered in future tests of gravity-mediated entanglement.

On a chain of exchange-coupled quantum dots a Heisenberg exchange pulse of area pi is a SWAP, so the parallel bubble-sort SWAP network of superconducting chains is native to exchange-only (EO) spin qubits, and any other pulse area fuses routing with an entangling interaction. We build a variational "bubble-sort exchange network" (odd-even transposition, one parameter per pulse) and study it as a Born machine read out by Pauli spin blockade. Exchange conserves total spin, so the reachable readout distributions are fixed by the total-spin content of the initial product state. For the two-spin singlet-triplet encoding we derive a selection rule -- outcomes with k triplet pairs are bounded by the initial weight in sectors S <= k (S = 0 excluded for k = 1) -- and prove by a transportation argument that it is also sufficient: the reachable distributions form the polytope cut out by the rule, and its total-variation floor is attained. Products of singlets and T0's forbid whole outcome classes; the Neel state forbids none; the three-spin EO code has no floor. We then distil, in noise-free simulation, next-token distributions of GPT-2 over restricted vocabularies into the network, with matrix-product-state (MPS) Born machines as classical control. At six logical qubits the three-spin chain reaches KL = 0.011 nat at depth N and 0.004 at 2N, below the bond-dimension-4 MPS; the two-spin chain from the Neel state reaches 0.014 at 2N and 0.004 at 3N, against 0.28-1.5 from singlet/triplet products for the first teacher. Final states lie largely outside the code space: leakage is a resource, not an error. No arrangement of disjoint pulses meets every pair in fewer than N-1 rounds, and at depth 2N the chain distils as well as a 2D array or non-local couplings. Sector-restricted simulation extends this to 10-14 logical qubits (up to 30 dots).

Classical simulation of quantum many-body dynamics is challenged by the rapid growth of operator complexity, particularly in higher dimensions where tensor-network methods become increasingly demanding. We develop state-adapted Pauli-weight propagation based on generalized $m$-body mean-field projections, which compress many-body observables into optimal low-body representations in a covariance geometry induced by the initial state. Combined with adaptive Krylov-like restricted Heisenberg dynamics, this provides an alternative to conventional Hilbert--Schmidt Pauli-weight truncation. We derive necessary and conditional sufficient bounds on low-body approximation accuracy using standard operator complexity measures and characterize possible dynamical failure mechanisms of the state-adapted method. Numerical benchmarks demonstrate substantial state-dependent accuracy gains, while identifying regimes of reduced accuracy or violations of Pauli spectral bounds. For a three-dimensional system of $80$ interacting spins, our method achieves strong body-order convergence, close agreement with independently converging tensor-network simulations, and substantially smaller sparse Pauli representations. These results establish state-adapted Pauli propagation as a promising approach to classical simulation of higher-dimensional coherent many-body dynamics.

We study interlayer exciton superfluidity versus layer separation in two-dimensional electron-hole bilayers at zero magnetic field and quantum Hall bilayers at total filling $ν_T=1$. Unscreened Hartree-Fock theory predicts coherence at every finite separation, with an energy scale decaying inversely with separation at large distances. We examine how screening, correlations, and spatial instabilities modify this prediction. At zero field, we solve the linearized gap equation with the full momentum and frequency dependence of the interaction screened within the random-phase approximation, without an imposed cutoff. The apparent plasmon enhancement of pairing in the ladder approximation is largely cancelled by the second-order crossed-rung correction. Static screening determines the leading pairing exponent in the controlled high-density limit at fixed separation. At large separation, the pairing scale falls exponentially with squared separation while the instability persists. Extending this result to fixed density assumes Fermi-liquid layers and higher-order dynamical corrections subleading to the static pairing interaction. At high field, we obtain an analytic uniform Hartree-Fock saddle point in the lowest Landau level, coherent at every finite separation. Within Hartree-Fock theory, its finite-wave-vector collective-mode instability favors an excitonic supersolid, distinguishing loss of spatial uniformity from loss of coherence. We conjecture that the quantum Hall bilayer evolves continuously toward weak pairing of composite fermions, with a scale far below the mean-field prediction at large separation. This suppression could produce an apparent critical separation at finite temperature without a ground-state quantum phase transition. The comparison separates the existence, energy scale, and spatial stability of interlayer coherence.

We examine how a finite many-body system can function as an effective charger for a single-qubit quantum battery, using the Lipkin-Meshkov-Glick model as a paradigmatic setting. As our figure of merit, we consider the battery ergotropy while explicitly resolving the energetic flows across the composite system. In the absence of intra-charger interactions, we show that the generation of non-zero ergotropy is controlled by the competition between collective coupling and spectral mismatch. We further demonstrate that even passive positive-temperature charger states can generate finite battery ergotropy, provided the charger is sufficiently large and sufficiently hot. Intra-charger interactions restructure the charger spectrum and qualitatively modify the available energetic pathways. While they can enhance the amount of energy accessible for charging, they can simultaneously divert energy into internal many-body and battery-charger interaction channels, producing an energetic impedance to direct charger-to-battery transfer. Consequently, battery ergotropy alone is insufficient to characterize an effective many-body charger: the useful work generated and its energetic provenance must be assessed together.

In this work we study the application of two-photon correlated quantum states for high-precision time estimation. To achieve this, photon pairs were fed into a Hong-Ou-Mandel polarization interferometer to generate N00N entangled states with $N = 2$. Two- and four-detector schemes were considered, and the achievable time estimation precision of each was studied, with particular emphasis on the system's Fisher information in each case. Our results reveal that using a four-detector scheme, enabling the measurement of both coincidence and photon-bunching terms, achieves the maximum precision given by the quantum Fisher information, without the need of characterizing system losses. We also show that correlations between repetitions arise due to systematic errors, limiting the precision enhancement that can be obtained by increasing the number of repetitions. Taking these correlations into account, we show that the four-detector scheme outperforms the two-detector scheme in the precision of time-delay estimation. With the experimentally determined calibration uncertainties, the four-detector scheme improves the dispersion by a factor of 2 for the repetitions performed, reaching up to a factor of 4 as both schemes approach their systematic floors.

Realistic non-Gaussian operations, which can be implemented by mixing a nonclassical Gaussian state with a Fock state at a beam splitter and then heralding on a photon-number-resolving detector, are known to improve phase estimation in a Mach-Zehnder interferometer. The existing studies have considered the single-mode squeezed vacuum for difference-intensity and parity detection, and the two-mode squeezed thermal state for parity detection alone as the initial Gaussian resources. However, a real squeezer in the lab actually produces single-mode squeezed thermal light, which has not been studied in a coherent-plus-resource interferometer. We take up this case and using the phase space Wigner picture, we obtain the heralded state produced by photon subtraction, addition and catalysis on a single-mode squeezed thermal resource, and evaluate the corresponding phase sensitivities. Single-photon catalysis, which is useless on squeezed vacuum, becomes a useful operation for any thermal occupation above $\nth\simeq0.2$, and since it heralds with a probability near one-half, it turns out to be the best success-weighted operation over the whole thermal range. In the vacuum limit our results reproduce the known hierarchy, where two-photon catalysis is the best operation. The quantum Fisher information computations confirms that thermal noise enhances the phase information encoded in the catalyzed state, demonstrating that difference-intensity detection closely approaches the ultimate precision bound across most operational regimes, and, together with a loss analysis, verifies the robustness of the effect.

The use of reinforcement learning (RL) in the design of quantum control strategies for pulse level control of NISQ era quantum devices is attracting growing interest. Model-free RL, not requiring preexisting knowledge of the physical system, acts as a black-box optimization tool well suited for noisy devices. In this work, we provide a simulation-based analysis of the performance of model-free RL for state preparation and qubit gate design in a challenging setup: indirect control of NV nuclear spins in a spin-bath. In particular, the spin-bath is modeled via the generalized cluster correlation expansion accounting for magnetic impurities and intra-bath interactions. We analyze the performance of the RL agents by performing simulations with minimally observable environments and noisy, sparse rewards as introduced in (Phys. Rev. X 12, 011059), and compare them to other state-of-the-art black-box optimization tools.

We completely classify connected Cayley graphs over finite abelian groups that exhibit perfect state transfer in Grover walks. First, we show that a Cayley graph over any finite group exhibiting perfect state transfer has valency $1$, $2$, or $4$. For valency $4$, we prove that an abelian Cayley graph $\operatorname{Cay}(Γ,S)$ exhibits perfect state transfer if and only if $S=\{a,-a,a+h,-a+h\}$, where $h$ has order $2$, and $4\nmid |Γ|/2$. Combining this characterization with the valency-one and valency-two cases, we explicitly determine all pairs $(Γ,S)$ for which $\operatorname{Cay}(Γ,S)$ exhibits perfect state transfer. Our results extend the classification of circulant graphs of valency at most four obtained by Kubota and Yoshino [Circulant graphs with valency up to 4 that admit perfect state transfer in Grover walks, \emph{J. Comb. Theory Ser. A.}, 216 (2025) 106064] to Cayley graphs over arbitrary finite abelian groups and to all valencies.

Quantum computing offers a promising approach to non-perturbative simulations of quantum field theories, particularly for real-time dynamics and systems affected by the sign problem. Yet translating continuum field theories into quantum computations remains a challenging interdisciplinary task. Here we introduce \texttt{Jianmu-Q}, a multi-agent framework that transforms natural-language descriptions of quantum field theories into quantum simulation workflows. Specialized agents handle theoretical formulation, lattice discretization, qubit mapping, and circuit design, while physical consistency checks and independent numerical calculations provide validation throughout the workflow. We benchmark the framework on three field theories of increasing complexity: the $(1+1)$-dimensional Nambu--Jona-Lasinio and Schwinger models, and a $(2+1)$-dimensional $\mathbb{Z}_2$ gauge theory. Across these systems, noiseless quantum-circuit simulations converge toward independent exact-diagonalization and tensor-network results, while selected circuits are executed on IBM quantum hardware, demonstrating an end-to-end, validation-guided approach to quantum simulation of field theories.

Far-detuned frequency allocations in fixed-frequency superconducting processors mitigate spectral crowding but constrain cross-resonance interactions at practical drive amplitudes. Here, we demonstrate that a single strong drive induces a large $XX-YY$ interaction in the far-detuned regime, while a weak second tone tunes the accompanying $ZZ$ phase. The interaction realizes a 150-ns $\sqrt{\mathrm{bSWAP}}$ gate, which can directly prepare a maximally entangled state from the ground state. For the implementations on the same qubit pair at matched drive strengths, cross resonance gives a shorter CNOT operation, while $\sqrt{\mathrm{bSWAP}}$ gives a 33% shorter SWAP operation with a higher IRB fidelity. The multilevel theory further predicts a regime where stronger driving can yield a speed advantage for CNOT as well, a possibility absent in the two-level model. As an application of the $XX-YY$ interaction, we also demonstrate two-spin squeezing beyond the standard quantum limit through two-axis countertwisting. The interaction realized here complements cross resonance and offers a route to efficient gate synthesis and quantum simulation of interacting spin systems.

Protecting quantum batteries from environmental noise remains a challenge. Using exact Burshtein-Kubo equations, we study a two-spin quantum battery with Dzyaloshinskii-Moriya (DM) coupling under indepen dent local longitudinal random telegraph noise (RTN). At a fixed effective noise scale, the DM-assisted slow switching protocol yields a superadditive transient ergotropy gain and near-maximal ergotropy during the initial charging stage, while the no-DM slow-switching control reaches comparable ergotropy only in a later revival. A finite superadditive region persists at fixed RTN amplitude, with protocol-dependent location and gain. In the Ising model, the enhancement is nonmonotonic in DM strength, with intermediate coupling giving near-optimal performance. Dressed-channel analysis associates this enhancement with changes in transition frequencies and longitudinal-noise matrix elements that reduce slow-RTN spectral weight. Superadditivity also persists in the tested anisotropic XY model.

The quantum Buridan's ass problem concerns a network of interconnected nodes in which transitions between the nodes are governed by the laws of quantum mechanics. In such situations interference between probability amplitudes plays a key role in determining whether the probability of leaving the initial node is large or small and also the speed at which the associated transitions occur. In this paper we extend this idea to consider transitions between one given set of coupled nodes and the remainder of the network. We have in mind a quantum analogy to changing an opinion, in which the initially occupied set of nodes is one opinion bubble, with the remaining parts of the network corresponding to a different opinion. We find that quantum interference again plays a crucial role in the dynamics. A further key component is the role of symmetry between the nodes and their interconnections, as it is symmetry that lies at the heart of the Buridan's ass puzzle. In the classical Buridan's ass paradox it is symmetry between competing alternatives that freezes the ass into indecision. In the quantum case, however, interference results in a far richer dynamics.

Hong-Ou-Mandel interference underpins many photonic quantum information protocols and is commonly characterized by a single visibility parameter. This quantity is typically obtained by averaging over a fixed coincidence window, thereby discarding details of the underlying temporal structure that are critical in continuous-wave processes. Four-photon interference with continuous-wave sources furthermore requires photon pairs with long coherence times, which we generate in microring resonators and measure with ultrafast time-resolved detection. Here, we model and resolve their interference and temporal structure by recording all four photon arrival times and mapping their relative delays onto a three-dimensional coincidence histogram relative to a trigger detection. The resulting structure preserves relative arrival-time correlations that are usually discarded and enables post-processed optimization of coincidence windows to trade off visibility against count rate. This method provides a general benchmark for continuous-wave sources in interference-based quantum network protocols.

Selected configuration interaction (SCI) obtains accurate many-body solutions by variationally diagonalising the Hamiltonian in a sparse, iteratively selected set of configurations, but can lose compactness when the target state has broad configurational support. We introduce selected stabilizer interaction (SSI), a fully classical, SCI-inspired method that instead iteratively constructs a nonorthogonal subspace spanned by a systematically enlargeable set of selected stabilizer states. A single stabilizer, generated by Clifford operations, can encode a structured superposition of (possibly exponentially) many configurations, shifting the relevant compression from configurational to stabilizer sparsity. We benchmark ground-state energies, fidelities, superposition degrees and required expansion lengths against exact diagonalization and equivalent SCI schemes for the transverse-field Ising, XXZ Heisenberg, and Hubbard models, finding particularly strong compression from the stabilizer representation in the spin models, and increasing advantage with system size for these systems. The results establish a proof of principle for heuristic selected stabilizer diagonalization, while also identifying particular challenges in symmetry handling and effective exploration of the stabilizer space.

Emergency-priority traffic signal control requires reducing emergency-vehicle delay while limiting disruption to ordinary traffic. This work investigates a finite-horizon QUBO formulation and compares Exact QUBO optimization, QAOA, CVaR-QAOA, a quantum machine-learning policy, fixed-time control, and max-pressure control in a three-intersection corridor. The study evaluates three traffic-demand regimes, examines the effect of the emergency-priority weight, and compares quantum solutions with the exact QUBO optimum. The optimization-based controllers achieved reliable emergency progression across all tested demand regimes, while max-pressure produced lower ordinary-traffic delay. Increasing emergency priority reduced emergency travel time but increased congestion, with diminishing improvements at larger weights. CVaR-QAOA reproduced the exact QUBO solution more accurately than standard QAOA, although the resulting differences in closed-loop traffic performance were comparatively small.

Together with a right-handed neutrino, the fermions of one generation of the Standard Model are labelled by five bits, a combinatorial structure tied to anomaly cancellation. We make this precise. Anomaly cancellation is the vanishing of a cubic form, the defining property of triorthogonal codes, the quantum error-correcting codes behind magic state distillation. Removing the right-handed neutrino gives a $[[15,1,3]]_p$ code for every prime $p$, including the Bravyi-Kitaev code for $p = 2$. For qutrits it is the unique shortest distance-three triorthogonal code.

We probe the conductivity of the lowest Landau level of a moiré-aligned monolayer graphene device by broadband microwave transmission through a coplanar waveguide ($\sim$50 mK, 15.4--18 T), isolating the longitudinal channel through a low-minus-high frequency band difference $D(ν)$. We resolve a series of minima in $D(ν)$ that drift with field along lines of fixed carrier density rather than fixed Landau filling, the hallmark of moiré-commensurate electron crystals. The strongest minimum is present at every field and matches no fractional quantum Hall or integer Hofstadter state. It lies at band filling $s=1/3$, one electron for every three moiré cells---the generalized Wigner crystal that DaSilva, Jung, and MacDonald predict as the most favorable fixed-density ($t=0$) commensuration. The weaker minima fall near neighboring commensurate fillings.

Understanding the microscopic environment of superconducting qubits is a central challenge for quantum technologies. Parasitic two-level systems (TLSs) of various microscopic origins are ubiquitous and limit qubit performance through decoherence, frequency drifts, and leakage. Recently, long-lived TLSs with lifetimes exceeding those of state-of-the-art qubits have been shown to induce correlated qubit dynamics, with direct implications for quantum error correction. Here, we perform wide-band quantum-jump correlation spectroscopy on flux-tunable transmon qubits and identify microscopic degrees of freedom that outlive the qubit by orders of magnitude. Pump-probe measurements at varying detunings from these objects reveal intrinsic lifetimes exceeding one second. Their weak coupling to the qubit, in the kilohertz range, is consistent with positional defects described by the standard tunneling model, without excluding other microscopic origins such as magnetic spin impurities or trapped quasiparticles. More broadly, these results establish superconducting qubits as a sensitive probe of exceptionally long-lived microscopic degrees of freedom and open a route toward their controlled access and functionalization.

Cold-atom quantum memories require a near-zero magnetic environment (residual field <1 microtesla) to mitigate Zeeman decoherence. Conventional three-axis active compensation suffers from inter-coil crosstalk and geomagnetic drift, which degrade the uniformity and long-term stability of the zero-field region. To address this, we propose a spatiotemporally cooperative feedback-controlled suppression architecture for magnetic interference. An integrally printed three-dimensional orthogonal coil frame mechanically suppresses inter-axis flux leakage. A spatial feedforward inverse matrix is introduced to algorithmically eliminate first-order cross-coupling. A dual-threshold hysteresis incremental-PI controller filters magnetometer quantization fluctuations and avoids frequent small jitter adjustments of coil driving currents. Hardware ablation experiments, long-duration stability tests and spatial magnetic-field mapping were conducted. Experimental results show that during a 714.4 s continuous steady-hold stage, the mean and maximum residual fields at the central point reach 0.112 microtesla and 0.224 microtesla, respectively. The overlapping Allan deviations of all three components remain below 5 nT for averaging times of 1.9-178.2 s. Based on differential-ferrofluid lattice-scan measurements combined with centre-constrained quadratic vector reconstruction and soft Maxwell regularization, a weak-field spatial distribution with an RMS variation of 5.65 microtesla is fitted within a spherical region of interest of radius 5 mm, where 67.5% of the model volume meets the sub-5 microtesla coverage criterion. For a prolate ellipsoidal region matching the atomic-cloud distribution with full axis lengths of 10, 5, and 5 mm, the upper field bound within 93.7% of the volume is 2.68 microtesla.