Quantum Computing Research Archive

Fault-tolerant quantum computers will depend crucially on the performance of the classical decoding algorithm which takes in the results of measurements and outputs corrections to the errors inferred to have occurred. Machine learning models have shown great promise as decoders for the surface code; however, this promise has not yet been substantiated for the more challenging task of decoding quantum low-density parity-check (QLDPC) codes. In this paper, we present a recurrent, transformer-based neural network designed to decode circuit-level noise on Bivariate Bicycle (BB) codes. For the [ [ 72 , 12 , 6 ] ] BB code, at a physical error rate of p = 0.1 % , our model achieves logical error rates almost 5 times lower than belief propagation with ordered statistics decoding (BP-OSD), and roughly 5 times larger than a most-likely error decoder. Moreover, while BP-OSD has a wide distribution of runtimes with significant outliers, our model has a consistent runtime and is an order-of-magnitude faster than the worst-case times from a benchmark BP-OSD implementation. On the [ [ 144 , 12 , 12 ] ] BB code, our model obtains worse logical error rates but maintains the speed advantage. These results provide initial evidence that machine learning decoders can out-perform conventional decoders on small QLDPC codes, but suggest more complex architectures and/or training procedures are necessary to scale to larger code sizes.

The quantum Zeno effect is a fundamental mechanism for implementing the effective dynamics of projected Hamiltonian and Lindbladian systems. It approximates the target projected evolution by interleaving Hamiltonian or Lindblad dynamics with quantum operations associated with the desired subspace. In contrast to the related Trotter product formula, the best-known convergence rate of the quantum Zeno effect is typically limited to order 1 / n . In this work, we improve this convergence rate by employing a multi-product formula, thereby achieving arbitrarily high-order convergence of the form 1 / n K + 1 . This yields an improved approximation scheme for Zeno-like expectation values via an efficient post-processing method. The approach combines a modified Chernoff lemma, an adapted Dunford-Segal approximation, holomorphic functional calculus, and Chebyshev interpolation. We illustrate the method with the bosonic cat code and also consider the broader class of systems governed by the Bang-Bang decoupling method.

There has been a surge of recent interest in the Wigner's Friend paradox, sparking several novel thought experiments and no-go theorems. The main narrative has been that Wigner's Friend highlights a counterintuitive feature that is unique to quantum theory, and which is closely related to the quantum measurement problem. Here, we challenge this view. We argue that the gist of the Wigner's Friend paradox can be reproduced without assuming quantum physics, and that it underlies a much broader class of enigmas in the foundations of physics and philosophy. To show this, we first consider several recently proposed Extended Wigner's Friend scenarios, and demonstrate that some of their implications for the absoluteness of observations can be reproduced by classical thought experiments that involve the duplication of agents. Crucially, some of these classical scenarios are technologically much easier to implement than their quantum counterparts. Then, we argue that the essential structural ingredient of all these scenarios is a feature that we call "Restriction A": that a physical theory cannot give us a probabilistic description of the observations of all agents. Finally, we argue that this difficulty is at the core of other puzzles in the foundations of physics and philosophy, and demonstrate this explicitly for cosmology's Boltzmann brain problem. Our analysis suggests that Wigner's Friend should be studied in a larger context, addressing a frontier of human knowledge beyond quantum foundations: to obtain reliable predictions for experiments in which these predictions can be privately but not intersubjectively verified.

We present efficient and practical protocols to measure the second Rényi entropy, whose exponential is known as the purity. Our approach is based on expressing the purity in terms of transition probabilities generated by an echo-type forward-backward evolution sequence, making it applicable to quantum many-body systems. Notably, our approach does not rely on random-noise averaging, a feature that can be extended to protocols to measure out-of-time-order correlation functions, as we demonstrate. By way of example, we show that our protocols can be practically implemented in superconducting qubit-based platforms, as well as in cavity-QED trapped ultra-cold gases.

Recent discoveries in asymptotically good quantum codes have intensified research on their application in quantum computation and fault-tolerant operations. This study focuses on the addressability problem within CSS codes: we ask what circuits might implement logical gates on strict subsets of logical qubits. With some notion of fault-tolerance, we prove several impossibility results: for CSS codes with non-zero rate, one cannot address a logical H , H S , S H , or C N O T to any non-empty strict subset of logical qubits using a circuit made only from 1-local Clifford gates.Furthermore, we show that one cannot permute the logical qubits in a code purely by permuting the physical qubits, if the rate of the code is (asymptotically) greater than 1/3 and the distance is at least 3. We can show a similar no-go result for C N O T s and C Z s between two such high-rate codes, albeit under a more restrictive assumption on the circuit, which we call "global" (though recent addressable CCZ gates use global circuits).This work pioneers the study of distance-preserving addressability in quantum codes, mainly by considering automorphisms of the code. This perspective offers new insights and potential directions for future research. We argue that studying this trade off between addressability and efficiency of the codes is essential to understand better how to do efficient quantum computation.

We prove that any n -qubit unitary can be implemented (i) approximately in time O ~ ( 2 n / 2 ) with query access to an appropriate classical oracle, and also (ii) exactly by a circuit of depth O ~ ( 2 n / 2 ) with one- and two-qubit gates and 2 O ( n ) ancillae. The proofs involve similar reductions to Grover search. The proof of (ii) also involves a linear-depth construction of arbitrary quantum states using one- and two-qubit gates (in fact, this can be improved to constant depth with the addition of fanout and generalized Toffoli gates) which may be of independent interest. We also prove a matching Ω ( 2 n / 2 ) lower bound for (i) and (ii) for a certain class of implementations.

Abstract Heat transfer involving phase change is computationally intensive due to moving phase boundaries, nonlinear computations, and time step restrictions. This paper presents a quantum lattice Boltzmann method (QLBM) for simulating heat transfer with phase change. The approach leverages the statistical nature of the lattice Boltzmann method (LBM) while addressing the challenges of discontinuous phase transitions in quantum computing. The method implements an interface-tracking strategy that partitions the problem into separate solid and liquid domains, enabling the algorithm to handle the discontinuity in the enthalpy–temperature relationship. We store phase change information in the quantum circuit to reduce information exchange between classical and quantum hardware, a bottleneck in many quantum applications. Results from the implementation agree with both classical LBM and analytical solutions, demonstrating QLBM as an effective approach for analyzing thermal systems with phase transitions. Simulations using 17 lattice nodes with 53 qubits demonstrate temperature root-mean-square errors of order 0.01 when compared against classical solutions. The method accurately tracks interface movement during phase transition.

Abstract As quantum computing progresses, variational quantum eigensolvers (VQEs) for ground-state preparation have become an attractive option in leveraging current quantum hardware. However, a major challenge in implementing VQE is understanding whether a given quantum system can even reach the target ground state. In this work, we study reachability conditions for VQE by analyzing their inherent symmetries. We consider a Rydberg-atom quantum simulator with global controls and evaluate its ability to reach ground states for Ising and Heisenberg target Hamiltonians. Symmetry-based conclusions for a smaller number of qubits are corroborated by VQE simulations, demonstrating the reliability of our approach in predicting whether a given quantum architecture could successfully reach the ground state. Our framework also suggests approaches to overcome symmetry restrictions by adding additional quantum resources or choosing different initial states, offering practical guidance for implementing VQE in quantum simulation architectures. Finally, we illustrate connections to adiabatic state preparation.

Abstract Gradient-based optimization is a key ingredient of variational quantum algorithms, with applications ranging from quantum machine learning to quantum chemistry and simulation. The parameter-shift rule provides a hardware-friendly method for evaluating gradients of expectation values with respect to circuit parameters, but its applicability is limited to circuits whose gate generators have a particular spectral structure. In this work, we present a generalized framework that, with optimal minimum measurement overhead, extends parameter shift rules beyond this restrictive setting to encompass basically arbitrary gate generator, possibly made of complicated multi-qubit interactions with unknown spectrum and, in some settings, even infinite dimensional systems such as those describing photonic devices or qubit-oscillator systems. Our generalization enables the use of more expressive quantum circuits in variational quantum optimization and enlarges its scope by harnessing all the available hardware degrees of freedom.

Intramolecular electron transport in biological systems is typically described as a diffusive hopping process, according to the semi-classical rate theories of Marcus and Hopfield combined with classical Pauli-type master equations. However, the possibility that non-trivial quantum mechanical effects could play a functional role in the transport dynamics in certain biomolecular processes has attracted increasing attention. Here, we extend the quantum mechanical model of open system dynamics by the Lindblad equation to a key biological component, the long chains of redox centers based on iron-sulfur clusters or heme groups that are widespread in many biological organisms, where they realize the cellular respiration. This approach allows to explore a wide range of physical parameters, showing key features of electron transport in these multi-domain protein structures. We pay particular attention to heat and entropy transfer between the electrons and the protein bath, which constitutes a benchmark of physical realism for the models. Electron currents, average transfer times and relative efficiency of the transport process are also explicitly characterized.

Electrostatically defined quantum dots (QDs) with layer-antisymmetric gating in Bernal-stacked bilayer graphene (BLG) open a local gap and generate a mass-like term with opposite sign in the two valleys, producing strongly valley-dependent scattering without magnetic fields, strain, or spin-orbit coupling. Building on this mechanism, we propose a tunable platform based on such QDs for valley-dependent electron optics in BLG. Using a four-band continuum model and a generalized multiple-scattering formalism, we analyze scattering of Gaussian electron beams from single- and multi-dot architectures and compute valley-resolved currents and angular profiles. A single dot produces distinct valley-dependent deflection, while multi-dot configurations enable enhanced control: identical-dot arrays act as valley splitters, whereas oppositely gated pairs function as valley filters. Combining these elements yields tunable generation, steering, and filtering of highly valley-polarized currents with strong suppression of forward transmission. The required energy scales, gate asymmetries, and device dimensions are within experimentally accessible regimes for dual-gated BLG, establishing quantum-dot arrays as a realistic platform for controllable valley-resolved electron optics.

Superconducting spiral inductors are emerging as key components for radio-frequency (RF) reflectometry, a widely used readout technique for semiconductor spin qubits. Future scalable quantum-computing architectures are expected to operate at elevated temperatures and magnetic fields, placing new demands on the performance and stability of superconducting circuit elements. Here, we present a systematic study of NbTiN spiral inductors under temperatures of several kelvin and magnetic fields approaching 1 T. By combining weakly coupled resonator measurements with independent two-port inductance extraction, we separate inductive and capacitive contributions to device behaviour and directly identify the origin of resonance shifts and quality factor degradation. Furthermore, we establish practical design metrics linking geometry, temperature sensitivity, and magnetic-field robustness. These results provide a general framework for benchmarking superconducting inductors and guiding the design of future RF-reflectometry circuits for practical quantum technologies.

Scalable quantum photonic technologies require deterministic sources of entangled photons that are compatible with established semiconductor manufacturing platforms. While self-assembled III--V semiconductor quantum dots are among the most promising sources of on-demand entanglement generation, their integration with silicon-based architectures remains a central challenge. Here, we demonstrate energy--time entanglement from a single InGaAs/GaAs quantum dot monolithically grown on a silicon substrate. Under coherent two-photon excitation, we achieve coherent control of the biexciton--exciton cascade, evidenced by Rabi oscillations and dressed-state formation. Using a four-channel Franson interferometer, we observe phase-dependent two-photon interference with visibilities up to $(64.0 \pm 7.0)\%$ for an 80 ps integration window (and $(49.4 \pm 1.9)\%$ for a 1600 ps window), approaching the threshold for Bell inequality violation at short time scales. These results establish monolithically integrated III--V-on-silicon quantum dots as promising sources of energy--time entangled photons for scalable quantum photonic technologies.

We theoretically investigate the linear and second-order nonlinear optical responses of valley-polarized bilayer graphene under uniaxial strain. Employing a low-energy effective Hamiltonian that incorporates trigonal warping and strain-induced anisotropy, we calculate the optical susceptibilities within the quantum kinetic formalism. We show that, while the second-order response vanishes in valley-balanced bilayer graphene owing to the cancellation of contributions from opposite valleys, a finite valley polarization lifts this cancellation and enables a net second-harmonic generation (SHG) signal. Uniaxial strain substantially modifies the nonlinear response by distorting the low-energy electronic structure and altering the pseudospin texture, producing a highly anisotropic SHG spectrum. Pronounced resonant enhancements occur at photon energies $\hbarω\approx E_f$ and $\hbarω\approx 2E_f$, associated with two-photon and one-photon interband resonances, respectively. Remarkably, changing the sign of the strain parameter reverses the direction of the induced second-harmonic current, providing a mechanically controlled switching mechanism for nonlinear optical transport. These results establish strain engineering as an effective route for manipulating valley-dependent nonlinear optical phenomena in bilayer graphene and suggest new opportunities for tunable mid-infrared photonic and valley-optoelectronic applications.

Quasiperiodic systems usually interpolate between extended, critical, and localized states as the quasiperiodic modulation is increased. Here we show that the magnetic Qi-Wu-Zhang Chern-insulator model realizes a distinct full-spectrum transition in which localization is avoided. For an irrational magnetic flux, the two-dimensional model reduces to a spinor quasiperiodic chain with a matrix onsite modulation controlled by the hopping amplitude $t_x$. When $|m+2|>t_y$, increasing $t_x$ produces the conventional extended-critical-localized sequence with a critical line at $t_x=t_y$. In contrast, when $|m+2|\le t_y$, the system changes from an extended phase to a critical phase at $t_x=|m+2|$ and remains critical even for stronger quasiperiodic modulation. Finite-size scaling of the average inverse participation ratio gives $\overline{\mathrm{IPR}}\sim q^{-α}$ with $0<α<1$ throughout this persistent critical regime. A dual transformation exchanging $t_x$ and $t_y$, together with a Lyapunov-exponent analysis, explains the phase diagram. Wave-packet dynamics further distinguish ballistic, anomalous-diffusive, and localized regimes. These results identify magnetic Chern-insulator systems as a natural platform for robust criticality and anomalous quantum transport.

We study scattering in noninteracting multi-terminal quantum wire junctions and show that junctions with dihedral symmetry can exhibit exact zero-reflection points for $N \ge 4$ terminals. By analyzing the scattering matrix, we identify these reflectionless points in the $(E,t')$ parameter space, where $E$ is the incident particle energy and $t'$ is the junction hopping amplitude. These points exhibit an even-odd dependence on $N$ and converge asymptotically to a common limiting value in the large-$N$ limit. We show that the reflectionless points are characterized by an integer winding number associated with the phase of the reflection amplitude, providing a topological description for their stability against weak on-site disorder. We also consider junctions with broken time-reversal symmetry and find that a magnetic flux can induce additional reflectionless points, including for the $N = 3$ case. For a four-terminal junction threaded by a $π$-flux, we identify a unique parameter regime in which the reflection amplitude vanishes over the entire energy band. Finally, we discuss experimental signatures through the behavior of Friedel oscillations and examine the stability of these reflectionless points in the presence of weak interactions.

We establish a coordinate-free differential geometric framework for anomalous transport in topological bands using the Hodge-de Rham decomposition of the Brillouin zone. Standard formulations face mathematical singularities (Dirac strings) when using the quantum Berry connection in bands with non-zero Chern numbers. Applying this decomposition to the Berry curvature 2-form isolates the quantized topological monopole flux from a globally smooth geometric 1-form proxy potential, $\mathcal{A}$. Substituting this regularized potential into semiclassical transport integrals yields distinct analytical advantages. For linear transverse transport, our cohomological decomposition enables an exact geometric derivation of Haldane's insight via the co-area formula, partitioning the response into a continuous Fermi sea topological background and a localized Fermi surface geometric line integral. For non-linear transport, this globally smooth proxy unifies the geometric description, reproducing the high numerical stability of scalar integration-by-parts techniques directly from its exact sector, accommodating arbitrary Chern numbers. By enforcing the continuous Coulomb-Hodge gauge ($δ\mathcal{A} = 0$) alongside vanishing harmonic holonomies over fundamental 1-cycles ($\oint_{γ_i} \mathcal{A} = 0$), we map the Hodge potential $\mathcal{A}$ to the Maximally Localized Wannier Function (MLWF) gauge in trivial bands, providing a non-singular computational proxy for topologically obstructed bands. Finally, we analytically demonstrate that solving the Hodge Laplacian for $\mathcal{A}$ zeroes the macroscopic Brillouin zone average (uniform $\mathbf{R}=0$ zero-mode) topological divergence, yielding a mathematically consistent covariant formulation that matches the algorithmic robustness of standard methods against discrete $\mathbf{k}$-grid noise.

Topological corner states in two-dimensional second-order topological insulators (SOTIs) are localized in real space. We numerically demonstrate that such localized topological corner states can mediate Andreev reflection when coupled to a superconducting lead. We consider a transport setup based on a two-dimensional honeycomb lattice, consisting of a normal lead, a central SOTI region, and a superconducting lead. The central SOTI region is described by the modified Kane--Mele model with an in-plane Zeeman field and hosts topological corner states in a diamond-shaped flake. Although the central region is insulating, the local density of states shows that incident electrons can turn the localized corner state into an extended scattering state, which forms a resonant tunneling channel to the superconducting lead. This process leads to a perfect Andreev reflection peak near zero energy. Away from this resonance, antiresonance dips appear in the Andreev reflection spectrum, and their positions can be tuned by the Zeeman field strength. We show that the suppression of Andreev reflection is caused by quantum interference and the imbalance between electron and hole dwell times in the central region. These results demonstrate that topological corner states can provide a resonant tunneling path to the superconducting interface and mediate Andreev reflection in second-order topological systems.

Exploring exotic quantum metallic states beyond Landau's Fermi liquid theory remains a central focus in condensed matter physics. Such non-Fermi liquid behavior is mostly observed near quantum criticality, yet growing attention is directed toward extended NFL phases with intrinsic quantum fluctuations rooted in the extended ground state. While these extended NFL states have been previously reported only in a limited set of d- and f-electron systems, realizing a single, highly tunable platform capable of exhibiting multiple resistance exponent values is essential for uncovering the connection between the resistance exponent and the dominant quantum fluctuations coupled to quasiparticles. However, corresponding experimental progress remains elusive. Here, we report the observation of tunable extended non-Fermi liquid behavior in twisted double bilayer graphene encapsulated by aligned hBN layers. This NFL phase spans a broad range of carrier densities and exhibiting a carrier density dependent resistance exponent. Combined with temperature dependent resistance, magnetotransport and differential resistance measurements, these findings support a scenario where strong quantum fluctuations emerge from the interplay between localized and itinerant carriers. Our work establishes a highly tunable platform beyond conventional frameworks to investigate the organizing principles of non-Fermi liquid physics manifested in diverse behaviors.

Abstract As a critical infrastructure for quantum internet, quantum entanglement distribution networks enable diverse quantum information applications. Among the existing architectures, the pump-management entanglement distribution network scheme exhibits remarkable scalability, functionality, and reconfigurability. However, its performance is hampered by the noise photons from concurrent spontaneous four-wave mixing (SFWM) processes and the unbalanced secure key rates (SKRs) across the network. Here, we propose a polarization manipulation scheme for pump-management entanglement distribution networks, enabling active control over the polarization states of the pump lasers and the generated single photons to optimize network performance. By utilizing orthogonally polarized pumps and polarization selection, the noise photons from other SFWM processes are effectively suppressed while preserving target entangled pairs, thereby significantly enhancing the SKR. Furthermore, our approach leverages the intrinsic efficiency differences of SFWM processes and a time-sharing method to achieve key rate equalization across the network. The performance enhancement is analyzed through theoretical analysis and numerical simulation. Our work resolves key bottlenecks in pump-management entanglement distribution networks, as well as establishes a powerful paradigm for performance optimization in future large-scale quantum networks.

Topological phases of matter are often realized in crystalline materials. To extend their understanding beyond perfect stoichiometry, we introduce a minimal model of a topological random binary alloy and show that the system realizes an exotic form of impurity-band engineering. We reveal that, in contrast to Wannier charge centers pinned by impurities in conventional semiconductors, doping a proximate quantum anomalous Hall insulator results in dopant-centric chiral current loops. The nature of such current loops is intrinsically tied to the properties of both the host and the dopant. We demonstrate that, even at dilute dopant density, these current loops can form topological domains in an otherwise trivial host and trigger a topological phase transition. On the other hand, doping a topological host having chirality opposite to that of the dopants can unexpectedly stabilize a metallic phase in which bulk transport is mediated by inter-domain edge modes.

Doping of transition metal oxides such as CaFe$_3$O$_5$ offers a controlled way to tune the interplay of charge, spin, and lattice degrees of freedom, yet local-probe studies remain difficult because strong correlations and dynamic charge-spin fluctuations obscure fine spectroscopic features in powder samples. Here, we employ quantum magnetometry based on nitrogen-vacancy (NV) centers in nanodiamonds impressed into an Mn-doped CaFe$_3$O$_5$ powder pellet to probe static and dynamic magnetic fields at the nanoscale across the weak ferromagnetic transition. The splitting and broadening of the optically detected magnetic resonance (ODMR) spectra exhibit an order-parameter-like increase by ~ 15 MHz upon cooling below the critical temperature, T$_{\rm c}$. Concomitantly, the spin-lattice relaxation rate, 1/T$_1$, exhibits a pronounced, divergence-like enhancement at T$_{\rm c}$, increasing by about one order of magnitude from its high-temperature value. Moreover, detailed lineshape fits of ODMR spectra together with the stretched-exponential NV magnetization recovery curves corroborate the proposed electronic phase segregation in charge-ordered and charge-averaged phases at the nanometric scales. The presented study demonstrates the viability of using nanodiamonds as a platform for nanoscale magnetic probing of strongly correlated matter, including phenomena such as electronic phase separation.

Over the past decade, semiconductor spin qubits have progressed from few-qubit demonstrations towards larger-scale devices fabricated in increasingly reproducible academic and industrial processes. This progress marks an inflection point: the central challenge is no longer to demonstrate high-fidelity operation in carefully tuned devices, but to discover, verify, and maintain stable operating conditions reliably across many interdependent controls, varied device geometries, and disparate material platforms. In this Perspective, we frame spin-qubit operation as a modular automation problem. We decompose the workflow into five modules: bootstrapping from minimal prior information, configuration tuning, virtualization of physical gates into effective control axes, qubit-level tuning, and an operation layer with drift-aware maintenance. Using recent demonstrations from our work and the broader community, we argue that scalability will depend on explicit interfaces between modules, standardized intermediate data products, and workflow-level metrics such as throughput, success probability, stability time, recovery time, and robustness. We close by outlining the infrastructure needed to move beyond isolated tuning demonstrations toward sustained operation: qubit-performance-aware feedback, reusable software and benchmark tasks, and tight collaboration among experimental, theoretical, and software efforts.

Scaling fault tolerant quantum computing is increasingly constrained by the limited bandwidth and power budget across the 4 K to room temperature (RT) interface. We present CryoZip, a cross stack cryogenic compression framework that cooperates with a lightweight cryogenic quantum error correction (QEC) predecoder to reduce 4 K to RT syndrome transmission under realistic, circuit level noise. CryoZip targets sparse syndrome vectors with a sliding window compression architecture sized under strict decoding latency constraints to maximize energy efficiency. We implement and evaluate the design in 22 nm FDSOI characterized at 4 K, using vector based power, performance, and area analysis to obtain realistic hardware data. CryoZip achieves up to 48x compression, 1.8x higher than state of the art compressors, across various QEC codes while delivering 4 to 26x energy savings. When paired with a QEC predecoder, it yields over 14,238x bandwidth reduction, while energy savings rise to 42x when accounting for realistic QEC interface overheads.

The controlled confinement of high-frequency acoustic phonons in semiconductor nanostructures has emerged as a key ingredient for functional nanophononic and hybrid quantum technologies. In this Review, we summarize recent advances that have established GaAs/AlAs acoustic nanocavities as a versatile and scalable platform for GHz-THz phonon engineering. Compared with alternative nanophononic platforms, GaAs/AlAs offers a particularly favorable combination of mature epitaxial growth, strong photoelastic coupling, and simultaneous optical-acoustic mode colocalization across the GHz-THz regime. We focus on distributed Bragg reflector (DBR)-based architectures, with particular emphasis on micropillar resonators enabling three-dimensional phonon confinement and strong colocalization of acoustic and optical fields. Recent developments in ultrafast optical techniques, including picosecond ultrasonics and Brillouin scattering, have provided unprecedented access to phonon dynamics, coherence, and dissipation at the nanoscale. These advances, combined with strong optophononic coupling, have enabled efficient coherent generation, detection, and manipulation of confined acoustic modes. We discuss key performance metrics, integration strategies, and remaining challenges, notably in acousto-optic transduction efficiency and scalable electrical control. Finally, we outline near-term perspectives for nonlinear phononics, hybrid quantum systems, and integrated phononic circuits, positioning GaAs/AlAs heterostructures as a robust and scalable platform for next-generation nanophononic functionalities.

We study heat rectification through a quantum two-level system asymmetrically coupled to two thermal baths, as described by the Ohmic spin-boson model. We evaluate the steady-state heat current using a tensor-network approach, which enables us to access the strongly correlated regime, and benchmark the results against analytical formulas in several limiting regimes, including the weak-coupling and incoherent-tunneling regimes. We identify a scaling regime where the studied system flows from an ultraviolet regime, at temperatures larger than the Kondo temperature, to an infrared regime, at temperatures lower than the Kondo temperature. By applying perturbation theory near the infrared fixed point, we find that the rectification ratio follows a universal power law. Our numerical results agree well with this analytical prediction. Our results provide a fundamental understanding of how dissipation-induced many-body physics affects heat transport.

Quantum entanglement is one of the most intriguing features of quantum mechanics. To investigate the entanglement between two excitons in a biexciton, an experimental technique called density matrix spectroscopy (DMS) has recently been developed. DMS combines stimulated emission tomography and pump-probe techniques to obtain a time-resolved density matrix of the polarization state of a photon pair emitted from the biexciton. The reconstructed density matrix is expected to encode information about the biexciton state and its entanglement dynamics, but the precise nature of this connection has remained unclear. In this paper, we derive an analytical relationship between the density matrix obtained by DMS and the biexciton state. In addition, we perform numerical simulations to compare the entanglement dynamics obtained by DMS with the biexciton's entanglement dynamics in a two-dimensional electron-hole system using an extended ionic Hubbard model. We find that DMS can partially capture the entanglement in the biexciton, in particular, the dynamics of the difference $S_{\mathrm{bi}} - S_k$, where $S_{\mathrm{bi}}$ is the entanglement entropy of the biexciton and $S_k$ is the entanglement in terms of the wavevectors of the excitons that constitute the biexciton. These results demonstrate the validity of DMS for obtaining information about the entanglement dynamics of the biexciton.

A subwavelength quantum-photonic circuit element should simultaneously generate nonclassical light, suppress plasmonic loss, and remain dynamically tunable. We show that an orthogonal plasmonic nanorod dimer can satisfy all three requirements. A phase-locked control polarization induces plasmonic refractive-index enhancement, driving the probe response toward a near-zero-extinction regime while simultaneously tuning the local second-harmonic parametric interaction. The resulting nonlinear plasmonic source operates in an absorption-suppressed regime and enables all-optical control of quantum correlations. We demonstrate switchable logarithmic negativity and single-mode nonclassicality, establishing a route toward actively tunable quantum-plasmonic circuit elements operating well below the diffraction limit.

We investigate the nonlinear optical response of a two-dimensional mesoscopic quantum ring subjected to a spiral dislocation, with emphasis on third-harmonic generation (THG). The topological defect is modeled through a torsion-induced deformation of space, which modifies the effective metric without introducing curvature. By combining the minimal-coupling prescription in curved space with a radial ring confinement and a perpendicular magnetic field, we derive the effective radial Schrödinger problem, obtain the bound states, and evaluate the nonlinear susceptibilities within the electric-dipole approximation. We show that the axial symmetry of the topologically deformed ring preserves the dipole selection rule $Δm=\pm 1$ and therefore suppresses second-harmonic generation, while THG remains allowed through multistep transition chains. The study is further expanded through three complementary analyses that can be implemented without changing the Hamiltonian: a dephasing-controlled study of spectral resolution, three-dimensional waterfall spectra showing the dependence on $β$ and $B$, and a channel-resolved decomposition of the THG amplitude. Together, these results establish the spiral dislocation as a robust geometric knob for tuning nonlinear optical activity in mesoscopic ring-shaped nanostructures.

Generative molecular design is shaped by simple proxy benchmarks for drug-like properties and models pretrained on large pharmaceutical datasets. This combination yields strong benchmark metrics but limits transferability to domains structurally distinct from drug discovery. To overcome this limitation and drive discovery toward real, scientifically grounded targets, we introduce the Nanotechnology Molecular Optimization (NMO) Benchmark, which bridges machine learning (ML) and quantum materials science. NMO acts simultaneously as a rigorous testbed for the ML community and a discovery engine for nanotechnology research. The suite replaces proxy oracles with quantum simulations and introduces strict protocols that prioritize scientific utility over leaderboard-oriented overfitting. The physics-based NMO tasks impose hard structural constraints and rugged fitness landscapes, posing fundamentally new requirements on generative models. Notably, advanced molecular optimization methods underperform much simpler approaches on the NMO tasks. We develop a new baseline method identifying the critical components to solve the NMO tasks, including a novel representation for modeling structural constraints and a domain-agnostic pretraining strategy to eliminate pharmaceutical dataset bias. Our results surpass state-of-the-art physical properties and reveal previously unknown structural motifs, offering new insights for the nanotechnology community and demonstrating that ML can drive genuine scientific discovery.

Decoherence is the biggest bottleneck in all quantum technologies. For nitrogen-vacancy (NV) centers in diamond, the loss of coherence is caused by the electron and nuclear spin bath of the diamond lattice. Here, we demonstrate that the spin bath - that typically causes decoherence - entangles the spin states of the NV electron and the host $^{14}$N nucleus. The many-body interaction between the $^{14}$N nucleus - electron - bath spins at an energy level anti-crossing occurring for an applied magnetic field orientation perpendicular to the NV axis is responsible for this effect. This is observed experimentally on NV ensembles via electron spin-echo measurements, where the echo envelope is modulated at the frequency of a $^{14}$N nuclear spin transition. Using numerical simulations, we show that the spin bath coupling to the NV centers is essential for observing this modulation. Due to the zero first-order Zeeman effect at the anti-crossing, the observed oscillations have long spin-echo coherence times, 2--3 times those at the parallel magnetic field orientation. The oscillation frequency is highly stable and robust against environmental fluctuations. These findings provide new opportunities for fundamental studies of many-body physics and quantum sensing.

At cryogenic temperatures, suspended single-wall carbon nanotube quantum dots act both as prototypical quantum dots as well as high-quality factor mechanical resonators. Single-electron tunneling enables reaching an ultrastrong electron-vibron coupling regime, where the coupling parameter exceeds the vibration frequency. Due to the high quality factors, a strongly nonlinear Duffing response is easily reached. Here, we quantitatively study the Duffing response parameters of such a device and their relation to Coulomb blockade oscillation. At the edges of single-electron tunneling regions, a local increase of the Duffing parameter corresponding to a stiffening spring is observed. Size and approximate scaling of the effect agree with single-electron tunneling phenomena, which however should lead to softening spring behaviour. Possible causes of these puzzling results are discussed.

Understanding the geometry of quantum Hall systems is a central challenge in modern condensed matter physics. We introduce a framework for probing the geometric structure of quantum Hall droplets by engineering the geometry of a dichroic probe and identifying the onset of "perfect elliptic dichroism", a regime in which the system responds exclusively to an elliptically polarized drive of a given chirality. This phenomenon provides a direct diagnostic of the droplet's intrinsic metric, and we show that it extends naturally to ideal Chern bands, where holomorphicity of the occupied states guarantees the vanishing of one chiral absorption rate with a quantized response for the other. In lattice realizations, such as the Harper-Hofstadter model, finite lattice-spacing corrections break the exact continuum metric description and give rise to a renormalized, emergent Landau-orbit metric; the probe ellipticity at which perfect dichroism is achieved then shifts accordingly, offering a direct spectroscopic window onto this lattice-induced geometric renormalization. Our results illuminate the rich geometric structure of quantum Hall phases and offer concrete pathways for observing these effects in quantum-engineered platforms.

Hall viscosity characterizes the geometric response of a quantum Hall droplet to deformations of the underlying metric, yet it has remained difficult to measure directly. We propose a spectroscopic probe based on circular dichroism, using chiral metric-sensitive drives -- implemented as rotating quadrupolar ("saddle") perturbations -- that effectively modulate the metric and couple to the generators of area-preserving deformations. The resulting dichroic signal directly measures the Hall viscosity, while frequency-resolved spectroscopy disentangles it from other excitations. A local formulation further enables spatially resolved markers of Hall viscosity applicable to both continuum and lattice systems. Our results open a direct route to measuring Hall viscosity in quantum-engineered platforms such as cold atoms in optical lattices.

Nonlinear transport has emerged as a sensitive probe of quantum geometry beyond the Berry-curvature physics of linear response. However, the intrinsic second-order dc response remains conceptually subtle: different quantum and semiclassical formulations can appear to give different static limits, with different assignments of Fermi sea and Fermi surface contributions. Here we resolve this ambiguity by developing a gauge-consistent density-matrix theory of intrinsic nonlinear conductivity in both the length gauge, where the electric field couples through the position operator, and the velocity gauge, where it enters through the vector potential. We show that the two gauges give the same adiabatic dc response when the same retarded continuation is used for all external frequencies and when the velocity gauge current includes all field-dependent vertices. The apparent Fermi sea terms cancel in the full expression, leaving a Fermi surface quantum geometric contribution determined by the band-normalized quantum metric. This result implies that a fully gapped insulator has no residual dc nonlinear Hall current in the adiabatic clean limit. The reactive part of the Fermi surface term agrees with the original semiclassical Berry-connection-polarizability response, while the dissipative Ohmic sector requires a more careful treatment of relaxation and impurity scattering. Our work establishes the length-velocity gauge equivalence for quantum geometric nonlinear response and provides a foundation for using nonlinear transport to probe magnetic quantum geometry, especially in PT-symmetric antiferromagnets.

Large-scale combinatorial optimization is a challenge for near-term quantum computing because dense Quadratic Unconstrained Binary Optimization (QUBO) formulations yield interaction graphs that exceed the limits of NISQ processors. This work introduces Hybrid Quantum Neighborhood Selection (HQNS), a hybrid framework mitigating this via stochastic frontier decomposition. Instead of encoding all N variables into a monolithic circuit, HQNS selects a compact frontier of F << N active variables per stage, freezing the rest into reduced QUBO coefficients. A multi-stage crawling procedure rotates these frontiers, letting local quantum subproblems refine a global solution. We evaluate HQNS on the Maximum Diversity Subset Selection Problem (MDSSP) across six scales, N up to 1000. Circuit burden is reduced from the dense QAOA requirement of O(N^2) two-qubit terms per layer to O(F^2) per stage, with total complexity governed by the number of stages and classical overhead. Benchmarks show that HQNS achieves competitive solution quality relative to parallel simulated annealing (SA) while maintaining bounded circuit width and stable QPU time. In the N=1000 benchmark over ten executions, HQNS preserves 99.9908% of the mean diversity score of an 11-restart parallel SA baseline, while reducing wall-clock time by 65.03%, peak CPU usage by 55.97%, and peak memory by 35.21%. Ablation shows performance depends on frontier size, warm-starts, CVaR filtering, and stochastic rotation. These results demonstrate that structured frontier decomposition makes variational optimization executable for dense QUBO instances unsuitable for direct QAOA on present hardware.

The quantum geometric phase intrinsically dictates the geometry, topology, and many-body correlations of electronic wave functions. While quantum geometric phases are conventionally inferred through momentum-space probes or macroscopic transport measurements, their direct visualization and quantification in real space have historically been restricted by the spatial averaging of bulk techniques. Scanning tunneling microscopy and spectroscopy (STM/STS) circumvent this limitation, leveraging atomic-scale spatial resolution and high energy sensitivity to resolve local electronic phase profiles directly. This review highlights recent progress across four representative methodologies: probing the Aharonov-Bohm (AB) geometric phase via nanoscale real space interferometry; extracting the Berry phase from defect-induced quasiparticle interference and wavefront dislocations; reconstructing the complex phase structure in symmetric systems, such as magic-angle graphene, using order parameter decomposition; and mapping the phase textures and topological defects of pair density wave (PDW) and charge density wave (CDW) in unconventional superconductors utilizing the numerical 2D lock-in technique. Together, these developments show how quantum phases can be translated onto real space and locally resolvable observables. Phase-resolved STM imaging provides stringent constraints on topological states of matter, symmetry-breaking patterns, and strong electronic correlations, outlining a robust framework for in situ phase engineering in quantum materials.

Local orbital magnetization is the field whose rotation generates the equilibrium current density. Unlike spin magnetization, a quantum-mechanical local formula consistent with both this current relation and the modern theory of bulk orbital magnetization has been missing. In this work, we derive a quantum-mechanical formula for the local orbital magnetization for non-interacting electrons by considering local-flux response of the grand potential. The local-flux response fixes the formula uniquely in two dimensions, whereas in three dimensions it selects a natural representative within a longitudinal ambiguity. Furthermore, coarse graining yields a natural local marker that generates the current to third-derivative order, and its site-position moment equals the orbital magnetic quadrupole moment of finite-size systems. We illustrate the obtained results with the Haldane model.

Physical reservoir computing offers an energy-efficient alternative to conventional neural networks, where the intrinsic memory capacity in the physical system plays a central role. We demonstrate that memory capacity can be engineered extrinsically in memoryless systems by exploiting the computational space-time tradeoff, substituting temporal memory with spatial degrees of freedom. Our approach utilizes multidimensional input nodes to function as a spatial memory axis, thereby removing the dependency on intrinsic history-dependent dynamics in the reservoir. We validate this framework through numerical simulations of a generalized quantum dot, whose discrete energy levels provide strong nonlinearity crucial for reservoir computing as well. By coupling this inherent nonlinearity with our extrinsic memory, we show that memoryless quantum reservoir can achieve high performance on both chaotic Mackey-Glass future prediction and nonlinear transformation tasks. Furthermore, by analyzing the geometry of the quantum state trajectories, we identify the physical mechanism underlying this memory emergence: extrinsic memory constructs a hysteresis loop within the quantum Hilbert space, and this loop becomes topologically stable when the evolution of the system state synchronizes with the input signal's frequency. Our work decouples reservoir computing from material-specific memory properties, significantly expanding the range of candidate systems for quantum neuromorphic computing.

Relative motion between interacting systems can generate emergent energy scales that are absent in isolated systems. While uniform motion can be eliminated by a Galilean transformation, relative motion between interacting systems generally cannot. In the presence of characteristic spatial structures, relative motion gives rise to a Doppler frequency scale determined by the characteristic wavevector of the excitation and the relative velocity of the system. This emergent scale provides a fundamental mechanism for driving nonequilibrium phenomena in moving systems. In particular, the emergent energy scale is determined by how the relative motion probes the spatial structure of the relevant excitation. In this tutorial, we illustrate these ideas using magnonic systems as a concrete platform. We first discuss motion-induced magnon transport between relatively moving ferromagnets, in which the Doppler frequency serves as an effective nonequilibrium bias in the perturbative regime. This mechanism produces magnon currents even in the absence of conventional driving forces such as temperature gradients or chemical potential differences. We then introduce motion-induced parametric instabilities. When the emergent scale becomes sufficiently large to resonantly create magnon pairs, the perturbative description breaks down, and the magnonic vacuum becomes unstable. Above a critical velocity threshold, spontaneous magnon-pair creation emerges, resulting in strongly enhanced transport and nonequilibrium dynamics. Connections to related phenomena, including quantum friction, Cherenkov emission, and Zeldovich superradiance, are also highlighted. The concept of an emergent energy scale provides a unifying framework for understanding transport phenomena and instabilities in quantum systems with relative motion.

Inferring microscopic Hamiltonians from experimental data is a central challenge in quantum materials and quantum simulation. In low-dimensional spin systems, exchange interactions are often assumed to be spatially uniform, despite structural and environmental inhomogeneities that can locally modify the coupling. Here, we leverage a local, length-independent machine learning methodology to reconstruct spatially modulated exchange interactions directly from inelastic scanning tunneling spectroscopy maps. We demonstrate this approach with nanographene spin chains, identifying both near-uniform and inhomogeneous regimes across the synthesized magnets. The reconstructed models quantitatively reproduce the experimental spectra and recover the correct scaling of the excitation gap with system size. Our results establish a general strategy to bridge local spectroscopic measurements with effective many-body Hamiltonians.

We develop a time-local nonequilibrium Green's function formulation for real-time dynamics in quantum systems coupled to superconducting leads. The superconducting lead self-energy is a strongly frequency-dependent matrix in Nambu space, giving rise to nonlocal memory kernels in the time domain. This makes direct propagation of the Kadanoff-Baym (KB) equations computationally demanding. To overcome this difficulty, we extend the auxiliary-mode expansion, originally developed for normal-metal leads, to Nambu-space self-energies. This allows us to decompose the superconducting lead self-energy into a finite number of exponential modes and to transform the KB equations with memory integrals into a closed set of ordinary differential equations. The resulting time-local equations enable efficient real-time simulations under general time-dependent bias voltages, superconducting phases, and one-body Hamiltonians of the central system, while retaining the memory effects induced by superconducting leads. As an application, we analyze voltage-quench dynamics in a superconductor-quantum-dot-superconductor junction and show that, after a dc bias is suddenly applied, the system evolves through a transient regime and relaxes to an ac Josephson periodic steady state. The resulting periodic steady-state current agrees with the Floquet Green's function solution, validating the present real-time formulation.

Cooperative emission is a collective quantum optical process that requires macroscopic phase coherence among coupled emitters. Recent observations of cooperative emission in QD superlattices have renewed interest in how such coherence emerges in nanostructured solids. Meanwhile, theoretical studies have long discussed the relationship between electronic delocalization and coherence, particularly whether delocalized states necessarily give rise to cooperative emission. This study addresses this question through power-dependent steady-state PL and time-resolved PL decay measurements. The findings indicate that, although the quantum resonance peak exhibits delocalized excitonic characteristics, it shows no signatures of cooperative radiation. In particular, neither superlinear intensity scaling nor power-dependent emission delay was observed, indicating the absence of cooperative-radiation signatures. This can be understood from two disorder-related aspects. Temperature-dependent spectroscopy reveals pronounced inhomogeneous broadening and low-temperature dark-exciton participation, pointing to intra-domain static disorder and exciton-state mixing. These effects collectively hinder the establishment of macroscopic coherence. The temperature dependence of the quantum resonance peak decay lifetime is consistent with two-dimensional exciton dynamics. This work provides direct experimental evidence that electronic delocalization can be decoupled from cooperative coherence in CdSe quantum dot superlattices.

We derive an equation describing domain wall motion in antiferromagnets under the influence of normal strain. From this equation, we find that the domain wall moves towards positions where $\varepsilon_{xx}$ is high and $\varepsilon_{zz}$ is low. Furthermore, each strain component leads to a different terminal velocity for the same strain profile. This difference arises because both strains affect the domain wall width in opposite ways: $\varepsilon_{xx}$ reduces the width, whereas $\varepsilon_{zz}$ increases it. The model is then compared with mumax$^+$ simulations for various strain profiles, including a strain gradient, an oscillating strain, and a Rayleigh wave. The comparison shows good agreement between the analytical and numerical results. Finally, we demonstrate the potential of standing surface acoustic waves as an error correction method in racetrack memory.

We present a novel quantum transport model for microwave-induced resistance oscillations (MIRO) where we prove that the instantaneous scattering rate is directly modulated by the velocity of the driven coherent state. This interaction peaks exactly at $ωt = 2nπ$, where the wave packets sweep through the impurity landscape at maximum speed, breaking time-reversal symmetry to generate a net direct current. Additionally, we introduce a dephasing architecture to explain amplitude saturation: a non-linear geometric dephasing ($\exp(-A/R_c)$) triggered when the displacement amplitude $A$ of the oscillating coherent state, approaches the cyclotron radius $R_{c}$. This perfectly captures the linear-to-sublinear power crossover at high intensities, offering a fully coherent description of non-equilibrium transport.

Surface acoustic wave (SAW) phonon coupling with nitrogen-vacancy (NV) center spins in diamond offers a promising platform for on-chip quantum phononic manipulations. Although an ensemble of NV centers coupled to a common SAW phonon mode enables superradiance and collective quantum control, achieving a tunable superradiant phase transition remains challenging. Here, we show that optically driving NV centers level transitions enhances the effective spin-phonon coupling, triggering a SAW phonon superradiant phase transition in the weak-coupling regime. We also demonstrate that above a critical threshold, the driving light rapidly switches on the phonon superradiance--a dynamic effect that persists in finite-number NV ensembles. Our results provide a controllable route to coherent phonon-NV spin manipulation in solid state quantum devices.

Attaching metallic contacts to transition metal dichalcogenide nanostructures and in particular to $\textrm{MoS}_2$ has posed significant challenges over the past years. For $\textrm{MoS}_2$ nanotubes and nanoribbons, a highly promising material for field effect transistors as well as quantum electronic devices, this is even more the case due to the small, curved surface. So far all attempts there have led to a wide scatter of contact resistances on the same chip. Recently, for quasi two-dimensional, flat $\textrm{MoS}_2$ flakes, the use of semimetals has led to a breakthrough, making transparent and Ohmic contacts possible. Here, we demonstrate the steps required to reproducibly fabricate contacts to single, vapor phase grown $\textrm{MoS}_2$ nanotubes and nanowires. All devices display finite room-temperature two-point resistances in absence of gating, with a median value of $340\,\textrm{k}Ω$ in a large fabrication series. A detailed analysis elucidates the impact of the different fabrication changes.

Rydberg states of atoms in vacuum are now well recognized as a resource for quantum technologies. Donors in semiconductors also display analogous states, which have been proposed for similar applications. While they benefit from permanent locations in their host crystals, electron-lattice coupling leads to much shorter excited-state lifetimes than for neutral atoms in vacuum. Here we provide a quantitative description of donor-phonon kinetics, creating a basis for engineering donor systems in realistic material stacks for quantum devices. Our theory incorporates both form factors for the Rydberg states, which given their large extents in real space provide strong selectivity in momentum space, and tabulated deformation potentials for all six phonon branches throughout the Brillouin zone. By confronting this framework with carefully controlled time-resolved free electron laser measurements, we show that the widely quoted position of the silicon conduction band minimum, $k_0$, is inconsistent with observed donor relaxation rates and that quantitative agreement is obtained for a value further from the X-point than commonly assumed. This stringent experiment-theory comparison establishes donor relaxation as a precision metrology for conduction band parameters and scattering processes in silicon, with consequences spanning from quantum devices to classical electronics.

We investigate the thermodynamics of interfacial spin transport within a normal metal/ferromagnetic insulator/normal metal ($\mathrm{NM/FMI/NM}$) trilayer heterostructure, where the central magnetic layer is described by the anisotropic quantum XXZ model. By employing the self-consistent harmonic approximation (SCHA) combined with a microscopic linear response formulation, we evaluate the interfacial spin-mixing conductance $g_{\uparrow\downarrow}$ across all spin regimes. We demonstrate that $g_{\uparrow\downarrow}$ uniquely decomposes into a coherent condensed component ($g_{\mathrm{cond}}$), driven by the macroscopic phase of the spin superfluid, and an incoherent fluctuation-driven term ($g_{\mathrm{fluct}}$) mediated by stochastic thermal magnons. Crucially, in the extreme quantum limit of $S = 1/2$, $g_{\mathrm{cond}}$ drops steeply and vanishes at a finite coherence temperature $T_{\mathrm{coh}}$. Conversely, the fluctuation-driven term $g_{\mathrm{fluct}}$ vanishes at $T = 0$, exhibits a characteristic $T^2$ quadratic scaling at low temperatures, and undergoes a systematic $1/S$ amplitude suppression as the macroscopic magnetization becomes robust. Our microscopic insights bridge the gap between quantum many-body fluctuations and macroscopic spin-superfluid hydrodynamics, providing clear foundational principles for optimizing long-range coherent transport in quantum spintronic devices.

We reveal that engineering electrode-coupling configurations can fundamentally reshape coherent transport phenomena in quasiperiodic quantum systems. Leveraging nonequilibrium Green's function theory, we systematically analyze charge and heat transport, as well as current fluctuations, in a magnetic-flux-threaded quasiperiodic Su-Schrieffer-Heeger ring with both symmetric and asymmetric multi-site reservoir couplings. Contrary to the conventional expectation that optimal transport is achieved near the homogeneous-hopping limit, our results reveal that multi-site lead coupling fundamentally reshapes the transport landscape, extending the regime of enhanced transport deep into the topological phase. Strikingly, asymmetric source-drain coupling induces a disorder-assisted conducting phase where quasiperiodic modulation enhances, rather than suppresses, charge and energy transport. Magnetic flux exerts a dual influence: it activates additional interference-mediated transmission channels that amplify transport while simultaneously suppressing the disorder-induced re-entrant conducting regime. Furthermore, we uncover a flux-driven migration of the optimal transport window with increasing disorder strength, shifting from the topological regime toward the trivial-hopping regime. This behavior highlights the intricate interplay among quasiperiodicity, dimerization, magnetic-flux-induced quantum interference, and the geometry of the system-reservoir coupling. Collectively, our findings position coupling engineering as a powerful paradigm for the rational control of nonequilibrium transport in quasiperiodic materials and chart a route toward quantum device configurations in which transport characteristics can be precisely tuned via the interplay of disorder, topology, and quantum interference.

We develop a quantum kinetic theory for Bloch electrons driven by a uniform dc electric field, extending the nonequilibrium density-matrix formalism beyond the non-crossing approximation. This extension is required to capture steady-state terms that are nominally zeroth order in disorder strength and compete with intrinsic band-geometric responses, as in anomalous Hall and related spin, orbital, and valley transport. Working in the length gauge with Gaussian white-noise disorder, we include impurity scattering to fourth order in the disorder potential. An iterative solution for the impurity-induced density-matrix fluctuations yields a connected $V^4$ collision integral after subtracting disconnected impurity pairings, thereby avoiding double counting. The resulting terms separate into self-energy corrections, ladder-type vertex renormalization, and crossed quantum-interference contributions. We clarify the correspondence between this density-matrix kinetic equation and the Keldysh formalism, and decompose the response into Fermi-surface and Fermi-sea components. As an application, we study the two-dimensional massive Dirac fermion model. We obtain analytical expressions for the single-particle lifetime, transport relaxation time, and longitudinal conductivity at the Born level, and then evaluate the anomalous Hall conductivity including crossed impurity processes. These processes generate an extrinsic contribution of order $τ^0$ that coexists with the intrinsic Berry-curvature term; for Gaussian white-noise disorder in this model, the $Ψ$-type contribution cancels while the $X$-type term remains finite. The formalism provides a consistent route for incorporating band geometry and crossed-disorder corrections into multiband transport, with applications to spin, pseudospin, orbital, and valley phenomena.

Spin-photon interfaces based on solid-state defects are key building blocks for scalable quantum networks and hybrid quantum platforms. Optimizing light-matter coupling in these systems requires precise knowledge of the optical transition dipole polarization, yet for many promising quantum emitters this quantity is hard to determine and therefore remains poorly characterized. Here, we develop a framework for reconstructing electric transition dipole polarization in spin-1/2 solid-state defects directly from ensemble spectroscopy. The approach combines the response of photoluminescence spectra to magnetic field, optical polarization, and strain. Applied to erbium ions in silicon, a particularly challenging system containing multiple crystallographic subsites, the framework identifies strain-induced shifts as the origin of asymmetric ensemble spectra and enables simultaneous determination of the optical dipole polarization and strain-orbital coupling tensor. The resulting model predicts how cavity-ion coupling depends on crystallographic orientation and magnetic-field direction, which we verify using single erbium ions coupled to a nanophotonic cavity. Together, these results establish a broadly applicable route for extracting microscopic properties of solid-state quantum emitters from ensemble spectroscopy and for engineering optimized spin-photon and spin-phonon interfaces.

Using on-chip microwave measurements, we investigate multilevel $π$-junctions formed by proximitized quantum dot (QD) in a germanium (Ge)/silicon-germanium (SiGe) heterostructure. In the multilevel regime, where several QD orbitals contribute simultaneously to superconducting transport, the Josephson ground state is no longer determined solely by the occupation of a single orbital. By combining DC transport and microwave techniques, we identify the qualitative signatures of multilevel $π$-junctions in both their gate-voltage dependence and microwave response. In particular, we observe combinations phase transitions that are sharp or smooth in gate voltage and which exhibit distinct inductive and dissipative signatures. Such multilevel Josephson transport has previously been observed primarily in exceptionally clean systems such as carbon nanotubes. Our results establish proximitized Ge as a platform for investigating hybrid superconductor/semiconductor physics and demonstrate the integration of gate-defined superconducting quantum devices with high-quality on-chip microwave resonators.

Variational Quantum Eigensolvers (VQEs) are central to quantum computing, yet testing them remains challenging due to the oracle problem: the ground-state energy they compute is itself unknown. Existing approaches, such as convergence-based testing, are unreliable and yield high false-positive rates due to optimisation instability. We propose METAMORPHQ, a metamorphic testing framework that derives test oracles directly from quantum mechanical properties of VQE circuits. Exploiting algebraic properties of parametrised rotation gates and diagonal Hamiltonians, we define five physics-based invariants that hold for any correct circuit and can be verified at initialisation without ground-truth outputs. Evaluated on 500 benchmark circuits with 2,469 mutants, METAMORPHQ achieves zero false positives and significantly improves diagnostic effectiveness (Youden's J = 0.57 vs. 0.02 for convergence testing). These results demonstrate that physics-derived invariants provide a practical, oracle-free foundation for testing quantum software, enabling reliable validation of both human- and LLM-generated circuits.

Interfacial exchange coupling plays a critical role in enabling novel phenomena in magnetic heterostructures, such as spin triplet superconductivity, quantum anomalous Hall effect (QAHE), and advanced spintronic functionalities. While microscopic characterization of this coupling is essential for elucidating the underlying mechanism, it remains technically challenging. Here, using spin-polarized scanning tunneling microscopy (SP-STM) and quasiparticle interference, we directly observed interfacial exchange coupling in a magnetic tunnel junction formed by an Fe coated tip and a Cr(001) surface. We found the ferromagnetic tip induces significant energy shift (up to 10 meV) in the spin-polarized surface state of Cr(001). This shift is highly sensitive to the tip-surface distance and the spin-alignment between Fe tip and Cr surface, which can be switched by external magnetic field. Our results demonstrate that extended 2D surface states can mediate strong exchange coupling across a heterojunction, enabling local control of interfacial exchange interaction induced phenomena.

Abstract Satellite-assisted entanglement distribution is a promising approach for realizing long-range quantum networking. However, the limited coherence time of existing quantum memories makes it challenging to obtain multiple event-ready entangled pairs between ground stations since one pair decoheres before the successful distribution of another. We demonstrate how this can be circumvented by pairing existing satellite-compatible spontaneous parametric down conversion (SPDC) sources with qudit-compatible quantum memories on ground. By operating the SPDC source as a source of time-bin encoded photonic qudits, simultaneous distribution of multiple entangled pairs between the ground stations can be achieved at a significantly higher rate than if the SPDC sources was operated as a source of photonic qubits. We find that for achievable coherence times of seconds and demonstrated satellite performances from the Micius satellite, the qudit operation leads to several orders of magnitude faster distribution rates than the qubit-based operation when more than one event-ready high-quality (Bell pair fidelity ⩾ 0.95 as well as for fidelity ⩾ 0.9 ) entangled pair is desired. To ensure high-quality entanglement distribution, we consider multiplexed quantum memory operation storage and, in the qubit case, we also consider storage cutoff times.

Abstract To progress in the characterization of noise for quantum computers, gate set tomography (GST) has emerged as a self-consistent protocol that accurately estimates noisy gates, state preparations, and measurements. In its original incarnation, GST improves estimation precision by applying gates sequentially, assuming the noise yields fixed completely-positive and trace-preserving (CPTP) maps independent of prior gate history. This ‘Markovian’ assumption can conflict with experiments, where time-correlated noise may induce non-Markovian dynamics, or slow drifts and cumulative calibration errors introduce context dependence, causing CP-divisible maps to vary with circuit depth. In this work, we address this issue for trapped-ion devices with phonon-mediated two-qubit gates. Using detailed microscopic modeling of high-fidelity light-shift gates, we tailor GST to capture the main source of context dependence: motional degrees of freedom. Rather than invalidating GST, context dependence can be incorporated into the gate-set parametrization, reducing sampling cost. Our results identify a promising research avenue that might be applicable to other platforms where microscopic modeling can be incorporated: the development of a context-aware GST.

Voltage-tunable Josephson junctions (VT-JJs) are an emerging element in superconducting quantum electronics with potential to expand the functionality of conventional designs. While VT-JJs are largely compatible with wafer-scale semiconductor processing, their integration into quantum circuits remains a challenge due to unmitigated semiconductor microwave loss. Here, a deep mesa etch process, wherein the epitaxial material is removed except the VT-JJ device, will facilitate the integration of VT-JJs with low-microwave-loss circuit elements by allowing these circuit elements to be placed directly on a low-loss substrate. A Germanium quantum well is grown by Molecular Beam Epitaxy (MBE) on a float zone silicon substrate with in-situ deposited aluminum contacts. This combination allows the formation of an oxide-free superconductor-semiconductor interface. The deep mesa etch process is optimized to produce a sidewall taper sufficient for continuous metal deposition from the substrate to the top of the mesa for electrostatic gate electrodes and interconnects. The fabricated Josephson junctions demonstrate gate-tunable supercurrents with a maximum critical current over 100 nA and critical-current normal-resistance product of $8.63~μV$. These results demonstrate a pathway toward improved integration of voltage-tunable superconducting circuit elements with quantum electronic building blocks such as couplers and qubits.

Quantum impurity models provide a paradigmatic setting for studying Kondo screening, boundary criticality, and impurity entropies. While these phenomena are well understood in unitary systems, their fate in non-Hermitian many-body settings remains largely unexplored. We study a $\mathscr{PT}$-symmetric quantum impurity model consisting of a unitary $SU(2)_1$ Wess--Zumino--Witten bulk coupled to two impurity spins through complex-conjugate boundary Kondo interactions. Using an integrable lattice realization with $\mathscr{PT}$-symmetric boundary impurities, solved by the Bethe Ansatz and benchmarked against finite-temperature matrix-product-state calculations, we determine the impurity contribution to the free energy and entropy. In the Kondo-screened regime, where the spectrum remains entirely real and the impurities are screened by many-body Kondo clouds, we find that the impurity entropy decreases monotonically from $\ln 4$ in the ultraviolet to $0$ in the infrared. This monotonic flow persists despite the nonunitary nature of the boundary interaction, which places the system beyond the standard assumptions of the $g$-theorem.

We show that Abelian and nonabelian gauge transformations are the analog of $W_\infty$ transformations for higher dimensional quantum Hall effect. The commutator anomaly and the extended algebra of such transformations on the edge modes of a droplet are obtained by purely topological arguments, basically utilizing the two-cocycle in the descent procedure for anomalies and using the fact that there is anomaly cancellation between the bulk and boundary actions. The method relies on the fact that bulk actions are easily constructed in general using the Dolbeault index theorem. The resulting algebras are shown to agree with explicit edge mode calculations for cases where they are available. We also comment on the similarities and differences in the nature of these transformations between two and higher dimensions.

We investigate extractable work storage in a capacitively coupled double quantum dot (DQD) quantum battery (QB) subjected to experimentally motivated detuning charge noise. The battery is modeled as two interacting charge qubits with an Ising-type capacitive coupling and is charged by resonant microwave modulation of the tunnel coupling channel. Detuning fluctuations are introduced as classical stochastic processes generated from a band-limited 1/f noise spectrum. For each noise realization, the evolution remains unitary, whereas decoherence and loss of contrast emerge after ensemble averaging. We analyze the total ergotropy, its population and coherent contributions, the energy basis populations, a passive ordering violation diagnostic, and the Jensen-Shannon coherence of the noise-averaged state. The results show that resonant tunnel coupling driving selects a dominant E0 <-> E3 population transfer channel in the interacting DQD spectrum. The dominant extractable work is stored in non-passive population distributions, in agreement with recent population ordering interpretations of ergotropy in QBs, while coherence accompanies and supports the resonant transfer as a transient dynamical resource. Detuning noise reduces the energy basis coherence amplitude and also weakens the population transfer pathway responsible for the dominant population ergotropy. This framework provides a noise-aware description of semiconductor QB charging based on extractable work rather than on injected energy alone.

We develop and characterize scanning transmission electron microscopy (STEM) capabilities within a scanning electron microscope (SEM) to investigate the effective lateral coherence of the electron beam (e-beam) in the specimen plane. Using single-crystalline Au flakes and a sample composed of a monolayer of graphene, we obtain high-quality selected-area electron diffraction (SAED) maps and convergent-beam electron diffraction (CBED) patterns, validating the systems ability to probe crystallographic information at an acceleration voltage of 30 keV. Building on these capabilities, we implement a method, which is adapted from techniques traditionally used in transmission electron microscopy, to measure the degree of lateral coherence of the e-beam in the specimen plane of the SEM. By analyzing interference between electrons with two different wave vectors separated by 0.031 per angstrom, we extract a lower limit for the degree of lateral coherence over 5% of the e-beam diameter of approximately 60%. These coherence values are sufficient to enable quantum-coherent electron-light-matter interaction experiments in the SEM.

Optically addressable valley degrees of freedom in transition-metal dichalcogenide heterostructures provide a powerful platform for valleytronic and quantum-optical functionalities. In moiré superlattices, interlayer excitons inherit valley-contrasting optical selection rules while acquiring long lifetimes, electric dipoles, and site-dependent optical responses. However, because conventional measurements typically probe time-integrated valley polarization, the dynamical origin of vanishing polarization has remained elusive. Here, we show that a nearly zero steady-state valley polarization in electrically tunable moiré excitons does not necessarily indicate fast valley relaxation. Helicity-resolved time-resolved photoluminescence reveals a temporal crossing between co- and cross-circularly polarized emission, indicating that helicity-opposite dynamical components coexist and compensate after time integration. A minimal two-channel model, representing A-like and B-like moiré emission channels with opposite optical selection rules and distinct effective decay/depolarization rates, reproduces the observed helicity crossing without invoking a single rapid valley relaxation process. Furthermore, two-dimensional gate-field maps show that the crossing time evolves systematically with electrostatic tuning, demonstrating that the hidden valley dynamics are electrically controllable. These results show that time-integrated circular polarization can give a false-negative indication of valley polarization in multichannel valley emitters.

A key challenge in developing Al/Ge heterostructures for quantum applications is Al-Ge interdiffusion. This process is facilitated by grain boundaries in polycrystalline films, which degrades interface quality and impairs device performance and reliability. Here, we present epitaxial growth of single-crystalline Al(111) on Ge(111) by molecular beam epitaxy, achieving an atomically flat and sharp interface. At the interface, a commensurate 7-Al-lattice/5-Ge-lattice epitaxial relationship is observed, which dramatically reduces the intrinsic lattice mismatch from 28.4% to about 0.1%. Interestingly, this well-ordered interface does not form below a critical thickness of 0.3 nm. Instead, Al initially nucleates as random clusters, which then transform into two-dimensional (2D) islands and, as Al deposition further increases, eventually develop into a continuous film. By optimizing the growth parameters, we have achieved an ultra-flat Al film with a surface root-mean-square roughness of about 0.16 nm and an ultra-thin continuous film with thickness of only 2 nm. These epitaxially grown Al-Ge heterostructures, with their atomically flat surfaces and sharp interfaces, provide a promising platform for studying topological quantum states.

Electron spin resonance in scanning tunneling microscopy enabled the study of electronic transitions of magnetic impurities on surfaces at the atomic scale. This ESR-STM technique allows to spectroscopically probe and coherently manipulate spins using an all-electrical method without oscillating external magnetic driving fields. Here, we aim to review recent advancements in ESR-STM. We will discuss possible fundamental mechanisms by which the electric field drives spin resonance based on Heisenberg exchange, Kondo scattering, and Anderson impurity models. We validate theoretical predictions against experimental observations, to understand how electronic correlations, spin exchange, and many-body effects manifest in ESR-STM signals. After reviewing coherent spin control in the STM junction, we discuss potential applications of the ESR-STM method for coherent multi-spin control which enables multiple-qubit operations. Finally, we address recent developments in coupled electron-nuclear spin systems, including hyperfine-resolved ESR spectroscopy, and the driving and polarization of nuclear spins in ESR-STM.

We predict a mechanism for the non-Newtonian behavior of a two-dimensional (2D) electron fluid due to the local Joule heating of electrons. Within this mechanism, the electron shear viscosity is a non-monotonic function of the velocity gradient. This means that 2D electrons form an unusual non-Newtonian fluid, either dilatant or pseudoplastic, depending on the flow regime. We construct and solve the hydrodynamic equations for a hydrodynamic velocity and a corresponding temperature profile for a Poiseuille-like flow geometry. We demonstrate that the considered non-Newtonian non-linearity induced by the local heating is apparently responsible for the nontrivial differential magnetoresistance observed for 2D electrons in ultra-high-quality GaAs quantum wells, so we conclude that a 2D non-Newtonian electron fluid is realized in these systems at high currents.

Hybrid photonic quantum computers, combining stationary matter qubits and flying photonic qubits, offer an intrinsically networked and resource-efficient route to large-scale, error-corrected quantum computation. Their core components are cavity-coupled matter qubits that act as light--matter interfaces, enabling: high-efficiency on-demand single-photon generation, stable near-unity photon indistinguishability and spin--multi-photon entanglement. Semiconductor quantum dots in microcavities are a leading platform for realizing such devices. Yet reaching the performance, reproducibility and spin-coherence thresholds for large-scale error correction remains a major challenge requiring industrial fabrication and control. Here we report thousands of monolithic semiconductor quantum-dot devices fabricated using a III--V pilot production-line process compatible with large-scale deployment. Systematic control of source parameters yields state-of-the-art efficiency and supports a path to optical losses below fault-tolerance thresholds. Using field-quadrature state reconstruction as a stringent joint test of efficiency and indistinguishability, we observe near-unity photon quantum purity stable over tens of minutes and a record single-photon Wigner-function negativity. We further demonstrate seven-partite spin--multi-photon entanglement and spin coherence extendable to microsecond timescales in the low-magnetic-field regime. Finally, photons from distant sources are as indistinguishable as photons emitted successively by a single source. These results establish foundry-compatible III--V quantum dots as a scalable platform for hybrid photonic quantum computing.

Drive-induced unwanted state transitions (DUST) are limiting both for microwave readout and parametric operations of superconducting qubits. Among them, measurement-induced state transitions (MIST) are due to intrinsic resonances described by the readout Hamiltonian. They were previously studied with a qubit linearly coupled to its readout mode, which constitutes the usual readout Hamiltonian. Since MIST can appear even at moderate powers, they limit the readout signal-to-noise ratio and the quantum non-demolition readout fidelity. In this work, we study the high-power readout regime in a different transmon readout scheme, implementing a nonlinear coupling called the cos  φ -coupling. This coupling stems from a transmon molecule circuit and has symmetry properties that suppress nonparity-conserving MIST. We succeed in performing multistate single-shot readout up to the fifth excited state of the transmon, which enables us to identify leakage pathways from the computational subspace. The measurements indicate that the system is free of MIST up to high powers, with more than 300 photons in the readout mode. The MIST can be controllably turned on by breaking the parity symmetry of the coupling using flux-tuning. These experimental results are corroborated by branch analysis and simulations of the classical chaotic dynamics, showing that the cos  φ -coupling is very robust to readout photons compared to the usual transverse coupling.

Quantum field simulators provide unique opportunities for investigating the dynamics of quantum fields through tabletop experiments. A primary drawback of standard encoding schemes is their rigidity: altering the theory, its coupling geometry, metric structure, or simulation time typically requires redesigning the experimental setup, which imposes strong constraints on the types of dynamics and theories that can be simulated. Here, we introduce the Optical Time Algorithm (OTA) as a unifying framework, enabling the efficient simulation of large classes of free quantum field dynamics using a single optical circuit design that separates the time from the Hamiltonian’s structure. By modifying the parameters of the optical elements, our method allows us to engineer timescales, coupling graphs, spacetime metrics, and boundary conditions, thereby facilitating the implementation of relativistic and nonrelativistic, real- and complex-valued, short- and long-range quantum field theories on both flat and curved spacetimes. We exploit the OTA’s configurability to investigate the spreading of quantum correlations in space and time for theories with continuously varying coupling ranges. Relevant features predicted by quantum field theory can be observed in systems with 10 to 20 modes under realistic conditions, paving the way for experimental implementations.

Abstract We introduce a quantum algorithm that integrates counterdiabatic (CD) protocols with quantum Lyapunov control (QLC) to address combinatorial optimization problems. This approach offers versatility, allowing implementation as either a digital-analog or purely digital algorithm based on selected control strategies. By examining spin-glass Hamiltonians, we illustrate how the algorithm can explore alternative paths to enhance solution outcomes compared to conventional CD techniques. This method reduces dependence on extensive higher-order CD terms and on classical optimization techniques, making it more suitable for existing quantum computing platforms. The combination of digital compression via CD protocols and the adaptable nature of QLC methods positions this approach as a promising candidate for near-term quantum devices.

Abstract In the field of quantum communication, investigating the practical security of systems is conducive to their deployments in real-world scenarios. In this paper, we identify and experimentally demonstrate a side-channel vulnerability within continuous-variable quantum key distribution (CV-QKD) arising from the zero-order hold (ZOH) effect in digital-to-analog conversion. As digital-to-analog converters (DACs) are indispensable for modulation in CV-QKD transmitters, this leakage constitutes an intrinsic and widespread risk. We show that the ZOH-induced spectral side lobes allow an eavesdropper to extract secret information without disturbing the main signal band. Experimental validation on a CV-QKD platform reveals a leakage of 2.68 Mbit/s against a generated secret key rate of 4.73 Mbit/s. Crucially, we propose a defense strategy that completely eliminates this vulnerability, effectively restoring the system’s implementation security. By resolving this fundamental hardware limitation, our work bridges the gap between theoretical models and practical engineering, paving the way for robust, standardized quantum communication networks.

Superconductor digital electronics and quantum computing with superconducting qubits are promising next-generation computing technologies. When cooled down or operated in the presence of a nonzero background magnetic field $B_r$, superconducting thin films comprising the circuits can trap magnetic vortices that can degrade circuit or qubit performance. In this work, we report a practical solution for eliminating flux trapped during cooldown in ambient magnetic fields, $B_r\leq 60$ $\upmu$T, based on controlled local thermal gradients and moats, etched holes in the superconducting films of the circuit. Thermal gradients created by integrated on-chip resistive heaters move vortices towards the moats, where they become trapped away from circuitry regions and pinning sites. Using magnetic imaging and electrical circuit readout, we demonstrate that this approach is capable of removing magnetic flux trapped during field cooling and magnetic flux nucleated by circuit operation. If used in an environment with basic magnetic shielding, this solution is capable of suppressing all magnetic flux in a large-scale circuit, overcoming one of the long-standing challenges preventing high-performance scalable computing using superconductors.

I propose a Hermitian extension of the Lorentz-symmetric Dirac theory by complementing the associated Hamiltonian with another \emph{masslike} anticommuting Dirac operator. The resulting theory manifests the iconic linear energy-momentum relationship in any dimension ($d$) and hence the emergent nodal quasiparticle excitations are named \emph{hidden-ordered Dirac fermions}, which are symmetry protected and their responses are analogous to those in original Dirac systems, however, in terms of a renormalized (due to the hidden ordering) Fermi velocity. Typically, such a hidden ordering pushes any quantum phase transition into an insulation toward even stronger coupling in any $d>1$. However, depending on the internal algebra between the candidate insulating order parameter and masslike Dirac operator, the hidden-ordering may survive or disappear near the corresponding itinerant quantum critical point. I construct lattice models for such hidden-ordered massless Dirac fermions and outline promising platforms (numerical and experimental) to test these predictions.

We demonstrate strong coupling between propagating spin wave modes and microwave photons in superconducting resonator-magnetic thin film hybrid circuits. By fabricating the resonator directly on yttrium iron garnet thin films grown on rare-earth-free Y$_3$Sc$_2$Ga$_3$O$_{12}$ substrates, we achieve strong coupling of both Damon-Eshbach and backward-volume spin wave modes to the resonator, with coupling strengths exceeding both the magnon and photon damping rates. Furthermore, we observe nonreciprocal spin wave radiation of the hybrid magnonic mode in the Damon-Eshbach configuration, highlighting the potential for incorporating intrinsic spin-wave nonreciprocity into hybrid magnonic systems. These results open new avenues for integrating spin-wave magnonics with cavity magnonics, and for harnessing spin waves for potential applications in quantum information science.

We report the temperature dependence of the substrate-induced magnetic anisotropy in continuous Ni thin films deposited at room temperature using magnetron sputtering on a 128° Y-cut LiNbO3 substrate. Ultrathin films exhibit a pronounced temperature dependence in magnetization, with as-grown films showing isotropic behavior and an unconventional hysteresis branch crossing at relatively low temperatures, whereas no branch crossing is observed in annealed films over the investigated temperature range, indicating suppression of the underlying mechanism. Temperature-dependent magnetization measurements show that post-deposition annealing establishes uniaxial anisotropy with well-defined easy and hard axes, whose strength evolves with temperature due to the nature of residual strain governed by both lattice mismatch and coefficient of thermal expansion (CTE) mismatch between the Ni film and the 128° Y-cut substrate, independent of film thickness for both 5 nm and 100 nm films. The emergence of this anisotropy following annealing indicates enhanced magnetoelastic coupling at the film-substrate interface, as the magnetic response begins to follow the anisotropic strain imposed by lattice mismatch and CTE mismatch.

Open quantum systems generally do not perfectly preserve phase coherence: coupling to uncontrolled environments requires a density-matrix description based on the Liouvillian framework beyond pure-state wave evolution. Realizing and probing such dynamics in a programmable platform is therefore essential for connecting coherent physics to realistic dissipative settings. Here we implement a tunable open-system quantum walk in a photonic mesh lattice, where controlled phase noise produces adjustable dephasing and non-reciprocal gain-loss imbalance provides an independently tunable non-Hermitian drive. This allows us to continuously interpolate between coherent quantum walks and incoherent classical walks, and to observe how directional transport evolves in the Liouvillian regime. Using non-Hermitian skin dynamics as a probe, we measure the center-of-mass drift over both the coherence and non-Hermiticity parameters, revealing a crossover from coherence-enhanced to decoherence-enhanced transport in quantitative agreement with quantum-channel simulations. We further program spatial and temporal interfaces to demonstrate interface accumulation and a long-time drift governed by the instantaneous channel. Our results establish a controllable photonic platform for simulating open quantum dynamics and show that decoherence can actively reshape non-Hermitian transport.

We investigate numerically the spin and transport properties of two-dimensional second-order topological superconductors (2D SOTSCs) hosting a pair of Majorana corner states (MCSs). First, we show that MCSs in the considered setup are characterized by a distinct spatial distribution of electronic spin polarization in the direction perpendicular to an applied in-plane magnetic field, with opposite signs for each MCS. Such a property can be used to label MCSs in a pair by their electronic spin. We propose a comprehensive spin-resolved transport protocol for measuring such a spin texture and further detecting the braiding (exchange) of a pair of MCSs, a crucial prerequisite for topological quantum computing. To be specific, we show that the magnitude of local conductance and the sign of nonlocal conductance are precisely linked to the sign of the electronic part of the MCS spin density and the spin polarization of the probe. Moreover, we show that the proposed technique can be used to detect the spin density profile of higher-energy quasiparticle states, e.g., edge states hosted in the SOTSC. We showed that all analyzed features are highly robust to strong static disorder , which makes our findings a clear experimental pathway to verify the spin structure of MCS and other quasiparticles hosted in SOTSCs.

Circular dichroism originates from symmetry breaking of material structure, leading to differential absorption of left- and right-circularly polarized light. However, circular dichroism in most materials is inherently weak and spectrally narrow, especially in the mid-to-far infrared. Here, we uncover giant infrared circular dichroism in the magnetic-field-forced Weyl semimetal Mn(Bi,Sb)2Te4, driven by extreme particle-hole symmetry breaking. Helicity-resolved magneto-infrared spectroscopy reveals circular dichroism exceeding 3000 mdeg (~130 mdeg/nm) with above-degree response extending over the 6-13 μm spectral range. The optical resonances are enhanced by a strong band nesting effect intrinsic to the Landau levels of type-II Weyl dispersion. A symmetry-based kp model reproduces these magneto-infrared responses and demonstrates that magnetization-induced asymmetric spin-orbit coupling generates particle-hole symmetry breaking, suppressing spin-up, parity-even wavefunction components in the valence Landau band and thereby producing pronounced optical helicity selectivity. Our findings establish particle-hole symmetry breaking as an effective route toward helicity-resolved optical control in quantum materials.

Thermal insulation remains an important technological challenge across the vast number of applications, from living quarters to quantum technology. Here, we exploit the size-dependent modification of the phonon density of states arising from phonon confinement in nanoparticles to fabricate a simple phonon rectifier. The smaller of the two connected nanoparticles imposes stronger phonon confinement leading to rectifying phonon transport. This concept is extended to the macroscale by constructing two overlapping layers of differently sized nanoparticles, thereby realizing a macroscopic phonon diode. Following the localized heat deposition by laser light, the temperature profiles across a phonon-diode were measured by infrared imaging. Although the rectifying strength is moderate, the abundance of optimization possibilities makes this method promising for ultra-low volume thermal insulation at both the nano- and macroscale

Parameter optimization is a central bottleneck in variational quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA). The classical optimizer must navigate a high-dimensional, non-convex parameter space under measurement noise. From a quantum software perspective, this process forms a multi-stage workflow: global exploration of the parameter space followed by local refinement within the hybrid quantum-classical loop. Most existing approaches, however, employ single-stage optimizers that do not separate these roles, which limits the use of complementary strategies. We propose MPE-Adam, a hybrid optimization framework that integrates multi-population evolutionary search for global exploration with Adam-based gradient refinement for local convergence. The method is structured as a modular component suitable for quantum software pipelines. We evaluate MPE-Adam on MaxCut instances generated from random 3-regular graphs with up to 22 nodes. The results show that MPE-Adam achieves higher approximation ratios and lower variance than evolutionary-only and SPSA-based baselines, with statistically significant improvements. These findings indicate that structured multi-stage optimization improves both solution quality and software-level flexibility in quantum applications.

We investigate Floquet-engineered topological phases in two-dimensional $d_{x^2-y^2}$-wave altermagnets irradiated by circularly polarized light in the off-resonant regime. These materials exhibit large momentum-dependent spin-splitting governed by distinctive magnetic symmetries. Using a lattice model combined with Floquet theory, we demonstrate that irradiation induces the light-tunable quantum anomalous Hall phases with the Chern numbers up to $\pm 3$. The resultant phase diagram is verified by calculating the anomalous Hall conductivity and also the edge modes inside the band gap of a nanoribbon version of the altermagnet. Our findings establish d-wave altermagnets as promising platforms for realizing nonequilibrium topological states of matter. The low-energy continuum limit of the lattice-based Floquet Hamiltonian results in a linear and higher-order-in-momentum spin-orbit couplings, and also a Zeeman-like magnetization, all arising from light-induced virtual photon processes. The resulting higher-order spin-orbit coupling generates the additional gapless Dirac points which, together with the high-symmetry gap-closings, yield enhanced Berry curvature and high Chern numbers. The light irradiation effectively breaks the static $d_{x^2-y^2}$-wave magnetic symmetry mixing in an isotropic photo-induced $s$-wave correction.

We theoretically examine the photon-assisted tunneling (PAT) in a double quantum dot (DQD) in parallel when one of the quantum dots (QDs) is irradiated by an AC field. First, we formulate the PAT in a single QD by solving the time-dependent Schrödinger equation using the scattering theory. The QD has an oscillating energy level, $\varepsilon(t)=\varepsilon_0+eV_{\mathrm{AC}}\cosωt$, and is connected to two leads by the tunnel coupling $Γ$. We show that the resonant tunneling takes place through energy levels of the polariton, $\varepsilon_0+N\hbarω$ ($N=0,\pm 1, \pm 2, \cdots$), when $Γ\ll \hbarω$ (PAT) and through the energy level $\varepsilon(t)$ when $Γ\gg \hbarω$ (adiabatic transport). Then, the scattering theory is applied to the PAT in the DQD in the presence of magnetic flux penetrating between the QDs. We observe the Aharonov--Bohm effect not only in the main peak ($N=0$) but also in subpeaks ($N \ne 0$), indicating coherent transport through the polariton states. Our theory is also applicable to the DQD in the three-terminal geometry. We demonstrate the phase measurement through the irradiated QD and show that the measured phase shift changes continuously from 0 to $π$ around both the main peak and subpeaks.

Abstract Quantum neural networks are increasingly distributed and deployed as third-party components, creating a supply-chain attack surface in which backdoors can be implanted during training yet remain difficult to detect under strict black-box constraints. In the probability-only minimal-interface regime, defenders often observe only post-readout class probabilities (or finite-shot frequency estimates), while shot noise and limited trusted clean data can obscure the small, targeted distribution shifts induced by poisoning. A trigger-agnostic black-box detector for this setting is proposed. The method elicits dose–response evidence by mixing a trusted clean pool with a suspect pool at progressively larger mixing ratios and tracking class-wise uplifts in predicted-class rates. To separate trigger-induced anomalies from static discrepancies between a model under test and a clean reference, we apply a difference-in-differences baseline alignment and stabilize the resulting response curves via Monte Carlo resampling under finite-shot sampling. Detection is formulated as a family of distribution-free one-sided sign tests across ratios and classes, with Holm–Bonferroni correction controlling the family-wise false-alarm rate; an effect-size gate yields a Detected/Pass verdict and a target-class estimate. We further characterize detection power as a function of the (unknown) prevalence of triggered inputs in the suspect pool. Experiments on 110 trained instances spanning quantum fast gradient sign method, quantum universal adversarial perturbation (QUAP), and patch-based backdoors on four-class MNIST subsets achieve an area under the receiver operating characteristic curve of 0.954 and an average precision under the precision–recall curve of 0.986. At the default operating point, the detector attains 0.906 sensitivity and 0.840 specificity, with most residual false alarms concentrated in QUAP clean controls under benign distribution shift.

Abstract Simulating non-Hermitian dynamics on quantum computers is often hindered by the decay of success probability and the instability of non-diagonalizable matrices. Here, we present contour-based matrix decomposition (CBMD), a rigorous and versatile quantum functional calculus framework for simulating non-Hermitian matrix functions. By generalizing the matrix Cauchy residue theorem, CBMD decomposes holomorphic non-Hermitian operators into an analytic infinite contour-residue identity, followed by finite truncation with controlled error to yield linear combinations of Hermitian components. For first-order dynamics, CBMD achieves optimal query complexity across all parameters, strictly matching the optimal performance bounds within the linear combination of Hamiltonian simulation paradigm. Beyond first-order systems, the framework naturally generalizes to complex operator functions, including second-order wave dynamics and non-Hermitian special functions such as Bessel and Airy evolutions. Furthermore, CBMD systematically suppresses the asymptotic growth of non-Hermitian components, yielding a significant reduction in the required number of amplitude amplifications compared to the naive scheme of combining monomials via linear combination of unitaries (LCU) after Taylor expansion. Notably, CBMD avoids explicit dependence on matrix diagonalizability, effectively mitigating the long-standing challenges associated with ill-conditioned eigenvectors and Jordan blocks. Our work establishes a systematic matrix calculus that bridges high-performance classical numerics and fault-tolerant quantum algorithms. It should be noted that CBMD inherits standard LCU overheads, and requires the target function to have a bounded growth order on the real axis.

We study the quantum Hall effect in a cubic lattice subjected to parallel electric and magnetic fields aligned along a crystal axis. The dual fields confine electrons in three dimensions with their classical orbits residing on the surface of a finite-size cylinder. In the quantum limit, the spectrum yields a three-dimensional generalization of the Hofstadter butterfly, featuring equidistant resonances near the spectral center and discrete levels near the boundaries. When the Fermi energy lies within these spectral gaps, the Hall conductance in the plane normal to the fields is quantized while other components of the conductance tensor vanish. Under open boundary conditions, this quantum Hall state exhibits topological chiral hinge modes protected by bulk Chern numbers. Our results offer a novel platform for studying the quantum Hall effect in both solid-state heterostructures and synthetic lattices.

We present a comprehensive study of quadrature squeezing in a quantum well laser based on a fully quantum Langevin approach. We compute the frequency-resolved squeezing map of the laser field and identify optimal squeezing curves, revealing, for the first time to our knowledge, both frequency-dependent squeezing and complex or hidden squeezing in a semiconductor laser. We further analyse the role of the linewidth enhancement factor (alpha factor) in the emergence of these features. Our results establish semiconductor lasers as a platform for the generation of non-classical light and open new perspectives for their application in quantum communication and sensing.

We propose altermagnetic semiconductors as a platform for field-free, all-electrically controlled spin qubits in gate-defined quantum dots. The momentum-dependent spin splitting of an altermagnet produces a Zeeman-like qubit splitting whose magnitude and sign are set by the dot ellipticity, enabling local frequency tunability without external magnetic fields or micromagnets. Because the splitting is tied to a fixed altermagnetic quantization axis, electric-field noise is longitudinally suppressed at leading order, while quantization-axis fluctuations couple transversely and therefore cause relaxation rather than pure dephasing. The compensated magnetic order also avoids stray fields, making the platform naturally compatible with superconducting resonators and dispersive circuit-QED readout through the qubit's spin-dependent electric dipole. Starting from an effective quantum-dot model, supported by a microscopic lattice model, we derive the single- and two-dot Hamiltonian models. We show that electric-dipole spin resonance enables single-qubit control, while tunable exchange and electrically addressable qubit frequencies realize fSim two-qubit gates. The same double-dot architecture also supports singlet-triplet qubits with electrical control of both exchange and splitting gradients, removing the need for micromagnets or nuclear-polarization gradients. These results establish altermagnetic quantum dots as a route to field-free spin qubits with intrinsic electrical tunability and enhanced dephasing protection.

Electronic excitations in solids are commonly described within a hierarchy in which the excitonic Hamiltonian is defined first and the lattice acts later through renormalization, relaxation, and dephasing. This picture assumes that the optically accessible excitonic manifold is already present at the moment of photoexcitation. Here we show that this assumption fails in a soft polar semiconductor. Using femtosecond coherent multidimensional spectroscopy on lead-halide perovskite nanocrystals, we observe quantum back-action between an electronic excitation and a collective lattice-polarization field that expands the excitonic Hilbert space in real time. The optical pulse first prepares an excitonic polarization, X1. A second configuration, X2, emerges only after the polaron field develops, while coherent X1-X2 coupling appears at later times. State formation and coherence formation are therefore resolved as distinct stages of quasiparticle formation. In contrast, CdSe quantum dots exhibit the conventional limit in which excitonic states and couplings are present at time zero and are only weakly perturbed by phonons. The observed diagonal and anti-diagonal splittings increase with nanocrystal size and correlate with radiative oscillator strength, opposite to expectations from simple quantum confinement. A dynamical polaron-field model describes the lattice polarization as an order parameter that expands the optically accessible manifold and generates time-dependent coherent coupling. These results show that strong system-bath coupling can actively create excitonic states and the coherent manifold in which they evolve.

Deterministic quantum light sources emitting at telecom wavelengths with vanishing fine-structure splitting (FSS) are essential components for scalable quantum communication. While self-assembled Stranski-Krastanov (SK) quantum dots (QDs) are high-quality emitters, their random positioning and shape-induced anisotropy typically limit their use in entangled-photon applications. In this work, we demonstrate site-controlled SK growth where InAs/InP QDs nucleate at the symmetric apexes of truncated InP nanopyramids. Confining adatom diffusion to a small, symmetric nucleation area suppresses anisotropic growth, promoting the nucleation of highly symmetric QDs with FSS reduced to values below our statistically validated resolution limit of $9.2~μ$eV. At the same time, lithographically defined nucleation sites enable deterministic control of the QD position, overcoming the limitations of conventional SK growth. The high structural quality of single symmetric QDs is evidenced by the single-photon character of the emission ($g^{(2)}(0)=0.07^{+0.27}_{-0.07}$) spanning the S, C, and L telecom bands, with no evidence of lithography-induced defects affecting emission dynamics. These results demonstrate that tailoring QD symmetry through nanopyramid growth engineering provides a route toward site-controlled emitters suitable for entangled photon generation and integrated quantum photonics devices.

Van der Waals materials are ideally suited for the implementation of high-frequency nanophononic resonators with atomically flat interfaces. Here, we present two versatile van der Waals-based nanophononic architectures: First, we introduce self-supporting nano-domes of WSe$_2$ as a scalable platform for the simultaneous generation of hundreds of high-quality nanoacoustic resonators with resonance frequencies in the 100 GHz range. Second, we engineer self-supporting nano-drums that reach record-high working frequencies for 2D-semiconductor transducers beyond 1 THz. Through optical pump-probe spectroscopy experiments and photoelastic linear chain model calculations, we gain a detailed understanding of the intricate interplay between phononic mode hybridization across heterostructures, the differences between modes close to the center and edge of the acoustic Brillouin zone, and the temporal structure of the photoelastic response. Both architectures have potential applications in low-cost nanoacoustic probing and the ultrafast modulation of quantum emitters in two-dimensional semiconductors. While nano-drums surpass the THz frequency barrier, nano-domes appear as an accessible, low-cost alternative for developing scalable nanophononic technologies.

We study the topological properties of a monitored Rashba chain along quantum-jump trajectories, investigating the persistence of the initial topological value of the disconnected entanglement entropy (DEE). We find that the DEE persists in its topological value for a time linear in the system size, even if the dissipation acts on the boundary and affects the topological Majorana modes. The reason for this phenomenon lies in the absence of particle conservation and in the degeneracy of the topological manifold, allowing the monitoring to let the system switch between different topological states -- alternatively creating and annihilating a Majorana mode -- while producing a poisoning of finite-energy ballistically propagating quasiparticles that eventually destroy the topological entanglement structure.

The cavity-magnon-qubit system has recently been demonstrated as a new platform for preparing macroscopic quantum states in magnonic systems. Here, we propose to prepare a two-mode magnonic cat state, which is also a non-Gaussian entangled state, based on this practical system involving two yttrium-iron-garnet (YIG) spheres and a superconducting qubit coupled to a common microwave cavity. By adiabatically eliminating the cavity and resonantly driving the qubit, an effective magnon-qubit conditional-displacement interaction is achieved. Further working in the magnon-magnon strong-coupling regime and considering two identical magnon frequencies and coupling strengths to the cavity, two hybridized magnon modes are formed, of which the bright mode is prepared in a cat state after a projective measurement on the qubit, while the dark mode remains in its initial vacuum state. Such a state corresponds to a two-mode cat state of two original magnon modes, which share strong non-Gaussian entanglement. We also discuss practical dissipation and dephasing effects on the cat state. The results indicate that strong nonclassicality and non-Gaussian entanglement are present in the two-mode cat state using fully feasible parameters.

We introduce a family of scalable planar fault-tolerant circuits that implement logical non-Clifford operations on a 2D color code, such as a logical T gate or a logical non-Pauli measurement that prepares a magic | T ⟩ state. The circuits are relatively simple, consisting only of physical T gates, C X gates, and few-qubit measurements. They can be implemented with an array of qubits on a 2D chip with nearest-neighbor couplings and no wire crossings. The construction is based on a spacetime path integral representation of a non-Abelian 2+1D topological phase, which is related to the 3D color code. We turn the path integral into a circuit by expressing it as a spacetime Z X tensor network and then traversing it in some chosen time direction. We describe in detail how fault tolerance is achieved using a “just-in-time” decoding strategy, for which we repurpose and extend state-of-the-art color-code matching decoders.

Displacement sensing is a fundamental task in metrology. However, the development of quantum-enhanced sensors that fully utilize the available degrees of freedom in many-body quantum systems remains an outstanding challenge. We propose many-body displacement sensing schemes that use spin-dependent squeezed (SDS) states—hybrid spin-boson states whose bosonic squeezed quadrature is conditioned on an auxiliary spin. We prove that SDS states are , i.e., their quantum Cramér-Rao bound saturates the Heisenberg limit. We propose explicit measurement sequences that can be readily implemented in systems such as trapped ions. We also introduce a scalable state-preparation protocol and numerically demonstrate the preparation of 8.7 dB of spin-dependent squeezing 15 times faster than the standard approach using second-order sidebands in trapped ions. The potential applications of our sensing protocols range from measuring single-photon scattering to searches for dark matter.

Abstract Designing superconducting quantum circuits involves optimizing the layout to achieve certain target parameters. This optimization process usually depends on iterative electromagnetic simulations, which are computationally expensive and require manual intervention to adjust the layout parameters. Here, we present a method to efficiently automate the optimization of superconducting circuits, which significantly reduces the need for manual intervention. The method’s efficiency arises from approximate nonlinear model-driven (ANMod) parameter updates, which are constructed from the user’s physical knowledge. Additionally, we provide a full implementation using the ANMod-method as an open-source Python package, QDesignOptimizer. The package automates the design workflow by combining high-accuracy electromagnetic simulations in ansys HFSS and energy participation ratio (pyEPR) analysis integrated with the design tool quantum-metal (formerly known as Qiskit-Metal). Our implementation supports modular and flexible subsystem-level analysis and is easily extensible to optimize for additional parameters. The ANMod-method is not specific to superconducting circuits; as such, it can be applied to a range of nonlinear optimization problems across science and technology.

Abstract Three-dimensional (3D) topological codes offer the advantage of supporting fault-tolerant implementations of non-Clifford gates, yet their performance against realistic noise remains largely unexplored. In this work, we focus on the paradigmatic 3D toric code and investigate its fault-tolerance thresholds in the presence of both Pauli and measurement errors. Two randomly coupled lattice gauge models that describe the code’s correctability are derived, including a random 2-form Z 2 gauge theory. By exploiting a generalized duality technique, we show that the 3D toric code exhibits optimal thresholds of p th X , M ≈ 11 % and p th Z , M ≈ 2 % against bit-flip and phase-flip errors, respectively. These threshold values show modest reductions compared to the case of perfect measurements, establishing the robustness of the 3D toric code against measurement errors. Our results constitute a substantial advance towards assessing the practical performance of 3D topological codes. This contribution is timely and in high demand, as rapid hardware advancements are bringing complex codes into experimental reach. Moreover, our work highlights the interdisciplinary nature of fault-tolerant quantum computation and holds significant interest for quantum information science, high-energy physics, and condensed matter physics.

Abstract Circuit optimization is a fundamental task for practical applications of near-term quantum computers. In this work we address this challenge through the powerful lenses of tensor network theory. Our approach involves the full characterization of the influence of individual gates on the entire circuit, a process we call quantum landscape tomography. We derive the necessary and sufficient requirements of this process and propose two implementations, respectively based on 2-unitary design and Clifford tableaux. The latter implementation strikes a convenient balance between the number of shots and the number of circuits needed for the tomography. Numerical simulations based on a realistic noise model demonstrate the advantage of our approach with respect to both gradient-free and gradient-based methods. Overall, our findings highlight the potential of quantum landscape tomography to enhance circuit optimization in near-term quantum computing applications.

Abstract One of the crucial aspects of current research in quantum information science is the identification and control of loss mechanisms in superconducting (SC) circuits. Although microwave measurements directly quantify device performance, additional techniques that probe quasiparticle excitations in SC films are needed to understand the microscopic mechanisms underlying dissipation and decoherence. Here, we present results from quasiparticle spectroscopy of Ta/sapphire films by measuring the Meissner-state magnetic susceptibility using a precision frequency-domain resonator specifically designed for thin films. We find direct evidence for additional low-energy excitations in samples with lower internal quality factors. These excitations are consistent with deep subgap states due to two-level systems, Yu–Shiba–Rusinov states near the gap edge, and perhaps other pair-breaking mechanisms. The developed non-destructive frequency-domain quasiparticle spectroscopy is a valuable addition to the quantum materials toolbox.

Abstract Pre-execution calibration is a major bottleneck for operating superconducting quantum processors, and qubit frequency allocation is especially challenging due to crosstalk-coupled objectives. We establish that the widely-used Snake optimizer is mathematically equivalent to block coordinate descent (BCD), providing a rigorous theoretical foundation for this strategy for qubit frequency allocation. Building on this formalization, we present a topology-aware block ordering obtained by casting order selection as a sequence-dependent traveling salesman problem (SD-TSP) and solving it efficiently with a nearest-neighbor heuristic. The SD-TSP cost reflects how a given block choice expands the reduced-circuit footprint required to evaluate the block-local objective, enabling orders that minimize per-epoch evaluation time. Under standard locality-type assumptions, such as local crosstalk or bounded interaction degree, the method achieves linear complexity in qubit count per epoch while maintaining comparable optimization performance. We formalize the calibration objective, clarify when reduced experiments are equivalent or approximate to the full objective, and analyze convergence of the resulting inexact BCD with noisy measurements. Simulations based on a physics-motivated error simulator show that the proposed BCD-nearest neighbor algorithm ordering attains comparable optimization accuracy at markedly lower computational cost than graph-based heuristics (BFS, DFS) and random orders, while also achieving optimization quality comparable to a genetic algorithm baseline. This method is robust to noisy objective-function evaluations and tolerant to moderate nonlocal crosstalk mismatch. These results provide a scalable, implementation-ready workflow for frequency calibration in near-term superconducting processors and, more broadly, for locality-structured calibration tasks in future scalable architectures.

Abstract Accurately computing the free energies of biological processes is a cornerstone of computer-aided drug design, but it is a daunting task. The need to sample vast conformational spaces and account for entropic contributions makes the estimation of binding free energies very expensive. While classical methods, such as thermodynamic integration and alchemical free energy calculations, have significantly contributed to reducing computational costs, they still face limitations in terms of efficiency and scalability. We tackle this through a quantum algorithm for the estimation of free energy differences by adapting the existing Liouvillian approach and introducing several key algorithmic improvements. We directly implement the Liouvillian operator and provide an efficient description of electronic forces acting on both nuclear and electronic particles on the quantum ground state potential energy surface. This leads to super-polynomial runtime scaling improvements in the precision of our Liouvillian simulation approach and quadratic improvements in the scaling with the number of particles relative to prior quantum algorithms. Second, our algorithm calculates free energy differences via a fully quantum implementation of thermodynamic integration and alchemy, thereby foregoing expensive entropy estimation subroutines used in prior works. Our results open new avenues towards the application of quantum computers in drug discovery.

Phase transitions are paradigmatic examples of emergent phenomena, in which symmetries present at the microscopic level can be spontaneously broken in the thermodynamic limit. Two primary physical mechanisms can drive this symmetry breaking: thermal fluctuations in classical phase transitions and quantum fluctuations in quantum critical phenomena. Here, we introduce $nonlocal$ $quantum$ $fluctuations$ as a new fundamental mechanism to drive phase transitions. We show that entanglement shared between environmental modes can induce a correlated symmetry breaking in remote systems, independent of their spatial separation. Using the framework of driven-dissipative phase transitions, we theoretically investigate a system composed of two nonlinear quantum resonators placed at arbitrarily large spatial separations, each coupled to independent local Markovian baths. We consider the regime in which remote environmental modes are prepared in broadband entangled states. We show that near the critical point, where the susceptibility to weak perturbations diverges, quantum correlations in the environments govern the system critical behavior. While these correlations manifest locally only as effective thermal fluctuations, at the global level they give rise to an emergent nonlocal phase transition, marked by the spontaneous symmetry breaking of a collective mode shared by the two remote systems.

Quantum Hall systems host emergent quasiparticles with unusual charge, spin, and statistics, such as fractionally charged anyons. Although transport measurements have revealed many of their collective properties, identifying and visualizing individual quasiparticles remain elusive. Here we use scanning tunneling spectroscopy (STS) to image quantum Hall quasiparticles in graphene. Within incompressible quantum Hall states, we observe spatial variation of Landau level energies originating from electrostatic potentials created by charged defects in graphene and the underlying hexagonal boron nitride (hBN). For surface and near-surface defects, the Coulomb potential lifts the degeneracy of Landau orbitals, producing discrete energy splittings that reveal Landau orbital wavefunctions. In quantum Hall ferromagnetic states, quasiparticles bound to defect potentials produce distinct spatial and spectroscopic signatures that serve as hallmarks of the presence and number of localized excitations. In the fractional quantum Hall regime at one-third filling, our theoretical calculations predict discrete spectroscopic changes associated with the sequential addition of localized anyons, with a three-anyon bound state quantitatively reproducing our experimental data at $ν= 5/3$. These observations establish spectroscopic fingerprints of quantum Hall quasiparticles and provide a pathway toward imaging and manipulating individual anyons in real space.

Fractional quantum Hall states host anyons, emergent quasiparticles with fractional charge and nontrivial exchange statistics. Controlling, trapping, and braiding anyons are central goals for both fundamental physics and topological quantum computation. A key step toward such control is understanding how anyons behave when confined in local potentials, where their internal structure can become relevant. Here, we use the scanning tunneling microscopy/spectroscopy (STM/STS) to study the excitation spectrum in integer and fractional quantum Hall states of monolayer graphene near individual charged impurities. In the integer quantum Hall states, the STS spectra show lifting of orbital degeneracy near defects, appearing as a band of discrete energy levels. In fractional states, (v=1/3 and 2/5), however, we observe an additional energy splitting of the lowest-energy spectral feature that occurs only when the chemical potential lies within a fractional gap and is absent in compressible or integer regimes. We attribute this to many-body configurations of anyons trapped by an impurity potential. Strikingly, numerical calculations show that the splitting requires an anisotropic confining potential, vanishing for a rotationally symmetric trap. The competing multi-anyon states carry nearly identical charge within the core of the potential but differ in how that charge is redistributed at larger radius. Our results establish local tunneling spectroscopy as a direct probe of anyon bound states, providing a key step toward understanding and controlling their behavior in confined geometries relevant for braiding and fusion.

Quasiparticles in fractional quantum Hall systems are anyons, carrying a fraction of the electron charge. Exchanging two of them gives rise to a fractional exchange phase. While the fractional charge and the braiding phase -- twice the exchange phase -- have been measured, the exchange phase itself has remained inaccessible. We study a quantum antidot embedded in a Fabry-Perot interferometer. Within a systematic non-equilibrium Keldysh treatment that consistently includes the occupation and level broadening of the antidot, we find that the transmission phase evolves non-monotonically when a gate voltage tunes the antidot through a resonance, in contrast to the monotonic evolution for electrons. The bare exchange phase can be extracted from the difference between the phase plateaus.

We studied the ac conductance of an $n$-InSb quantum well structure using acoustic methods in magnetic fields up to 18 T and at temperatures ranging from 20 to 500 mK. We attribute the unusual magnetic field dependences of surface acoustic wave (SAW) attenuation and velocity observed in the experiment to the presence of a conducting layer parallel to the quantum well in the sample. We successfully separated the contributions from both the quantum well and the shunting layer, enabling the identification of their distinct conduction mechanisms. Furthermore, by employing the coincidence technique, we determined the electron g-factor in the quantum well and investigated its dependence on the degree of spin polarization.

Active matter comprises particles that extract energy from their local environment and convert it into motion. Although active particles have been miniaturized down to the nanoscale, realizing activity at the fundamentally smaller scale of individual atoms remains an open challenge, where quantum effects become increasingly relevant. Here, we experimentally demonstrate that individual Cs-133 atoms confined in an optical dipole trap extract energy from an ultracold bath of Rb-87 atoms via quantum-mechanical spin interactions and convert it into active motion. We quantitatively reproduce the resulting dynamics using a parameter-free active Langevin model derived from kinetic theory and support it with event-driven Monte Carlo collision simulations. The microscopic origin of activity is identified as quantum spin exchange, which transfers discrete internal spin energy into kinetic motion. Our work establishes a quantum-enabled route to active matter at the fundamental size limit of single atoms and opens perspectives for exploring the interplay of activity, quantum physics, and mesoscopic non-equilibrium thermodynamics.

We propose gate-defined spin qubits in electrostatically confined altermagnetic quantum dots. Elliptical confinement of the $d$-wave altermagnetic structure produces a low-energy doublet with opposite spin polarization. For the range of parameters used here, the qubit states energy gap lies in the microwave range while the leakage gap remains in the meV range. Even without spin-orbit coupling, time-dependent simulations show that a phase-controlled quadrupolar gate drive about a fixed bias point implements $X_{π/2}$ and $X_π$ rotations by resonantly modulating the confinement anisotropy. We extend the study to two-qubits using a double quantum dot. We show that the double quantum dot spectrum can be cleanly projected onto isolated quantum dot product states with a nonzero nonlocal Pauli block in the effective logical two-qubit Hamiltonian. Resonant central-barrier modulation then drives the logical two-qubit component close to a maximally entangled state. These calculations show anisotropic altermagnetic quantum dots as a route to locally gate-controlled spin qubits without requiring spin-orbit coupling.

Introduction In biochemical processes development and analysis, binding energy, the energy released when a small molecule docks into a protein’s active site, determines how strongly a compound, such as a ligand, interacts with its protein target. Early-stage computational prediction of this quantity helps research teams prioritize candidates before committing to resource-intensive laboratory testing. Conventional methods in chemistry handle this well for small systems, but face known accuracy limitations in strongly correlated molecular environments and incur growing computational costs as system size increases. Addressing both challenges is the motivation for this work. This post describes a project by Classiq to build and validate a complete quantum-classical pipeline. The project was conducted as part of Dimension X, an open innovation challenge by Hatch, an innovation center in Singapore. The goal of the project was to demonstrate a quantum-classical pipeline for computational chemistry and binding energy estimation. The calculations were conducted on AWS cloud infrastructure using Amazon Elastic Compute Cloud (Amazon EC2) on a c6i.16xlarge instance with 64 vCPUs and 128 GB of memory. The pipeline combines high-performance parallelized Density Functional Theory (DFT) calculations with a variational quantum eigensolver (VQE), made accessible through the Classiq platform. The result is a workflow that uses AWS resources to handle the heavy classical computation and quantum computing to account for quantum correlations in the calculations, increasing accuracy beyond what DFT alone provides. What you will learn from this post: How ligand-protein interactions and binding energy estimation are formulated as a quantum chemistry problem How Classiq built and ran a hybrid classical–quantum workflow using AWS compute infrastructure. How the fragment-environment embedding approach keeps the quantum problem tractable as system size grows The Problem: Why Binding Energy Pred

We present universal properties of anticoncentration in noisy quantum circuits at finite depth. We develop a generic framework for single- and multi-qubit noise channels in the weak-noise limit and introduce an effective description in terms of a . Within this weak-noise regime, we show that distinct noise mechanisms act in a quantitatively similar way, yielding a universal distribution of bit-string probabilities that is largely independent of the microscopic noise channel and of the circuit architecture. We identify three depth-dependent regimes, each characterized by a distinct scaling of cross-entropy benchmarking ( XEB ) with rescaled depth. In the shallow-depth regime, noise effects are perturbatively small; in the intermediate regime, circuit-induced fluctuations and noise compete on equal footing; and in the deep-depth regime, the output distribution becomes effectively classical, up to corrections that are exponentially small in the noise strength. We provide quantitative predictions for anticoncentration in generic finite-depth circuits and benchmark them against numerical simulations, finding excellent agreement even at shallow depths. Moreover, we show that, contrary to previous expectations, the late-time value of XEB provides direct access to the global circuit fidelity, even at large noise strengths. Our results are directly applicable to current quantum processors and demonstrate universal behavior beyond the pure random-matrix-theory regime, which only emerges at asymptotically large depths.

Non-Gaussianity is a key resource for achieving quantum advantages in bosonic platforms. Here, we investigate the : a non-Gaussianity monotone that satisfies remarkable operational and resource-theoretic properties. Mathematically, the symplectic rank of a pure state is the number of symplectic eigenvalues of the covariance matrix that are strictly larger than those of the vacuum. Operationally, it (i) is easy to compute, (ii) emerges as the smallest number of modes onto which all the non-Gaussianity can be compressed via Gaussian unitaries, (iii) lower bounds the non-Gaussian gate complexity of state preparation independently of the gate set, (iv) governs the sample complexity of quantum tomography, and (v) bounds the computational complexity of bosonic circuits. Crucially, the symplectic rank is nonincreasing under postselected Gaussian operations, leading to new no-go theorems for Gaussian conversion. Remarkably, this allows us to show that the resource theory of non-Gaussianity is irreversible under exact Gaussian operations. Finally, we show that the symplectic rank is a robust non-Gaussian measure, explaining how to witness it in experiments and how to exploit it to meaningfully benchmark different bosonic platforms. In doing so, we derive lower bounds on the trace distance (resp. total variation distance) between arbitrary states (resp. classical probability distributions) in terms of the norm distance between their covariance matrices, which may be of independent interest.

Abstract Spin-squeezed states are metrologically useful quantum states where entanglement allows for enhanced sensing with respect to the standard quantum limit. Key challenges include the efficient preparation of spin-squeezed states and the scalability of estimation precision with the number N of probes. Recently, in the context of the generation of spin-squeezed states via coupling of three-level atoms to an optical cavity, it was shown that increasing the atom-cavity coupling can be detrimental to spin squeezing generation, an effect that is not captured by the standard second-order adiabatic cavity removal approximation. We describe adiabatic elimination techniques to derive an effective Lindblad master equation up to third order for the atomic degrees of freedom. Numerical simulations show that the spin squeezing scalability loss is correctly reproduced by the reduced open system dynamics, highlighting the role of higher-order contributions. Furthermore, we conjecture an extension beyond leading order of the adiabatic elimination technique to the case of conditional dynamics under quantum non-demolition continuous measurement and fast cavity loss, whose reliability is again confirmed by numerical simulation of the dynamics and the corresponding behavior of spin squeezing as a function of N .

Abstract Quantum optimal control plays a vital role in many quantum technologies, including quantum computation. One of the most important control parameters to optimise for is the evolution time (pulse duration). However, most existing works focus on finding the shortest evolution time theoretically possible without offering explicit pulse constructions under practical constraints like noise in the system. This paper addresses these limitations by introducing an efficient method to perform the chopped random basis optimisation in the presence of noise, specifically when the noise commutes with the gate Hamiltonian, i.e. when the unitary and dissipative parts of the Liouvillian commute. This noise-aware approach allows for direct optimisation of the evolution time alongside other control parameters, significantly reducing the computational cost compared to full noisy simulations. The protocol is demonstrated through numerical simulations on state-to-state transfer and gate compilation problems under several noise models. Results show that the optimised fidelity has a strong dependence on evolution time due to noise, drift Hamiltonian, and local traps in optimisation, highlighting the necessity of optimising evolution time in practical settings that can lead to a substantial gain in the fidelity. Our pulse optimisation protocol can consistently escape from many local minima in all of our examples. We hope that our protocol can be the start of many more works on the crucial topic of control pulse time optimisation in practical settings.

Abstract Trapped ions are one of the most promising quantum-information-processing platforms, yet conventional entangling gates mediated by collective motion remain slow and difficult to scale. Exciting trapped ions to high-lying electronic Rydberg states provides a promising route to overcome these limitations by enabling strong, long-range dipole–dipole interactions that support much faster multi-qubit operations. Here, we introduce the first scheme for implementing a native controlled–controlled-Z gate with microwave-dressed Rydberg ions by optimizing a single-pulse protocol that accounts for the finite Rydberg-state lifetime. Under realistic conditions, the resulting gate achieves fidelities above 97 % with execution times of about 2 μ s at cryogenic temperatures, making it more than 8 μ s faster than standard decompositions into one- and two-qubit gates. To explore the potential of trapped Rydberg ions for fault-tolerant (FT) quantum error correction (QEC), and to illustrate the utility of three-qubit Rydberg-ion gates in this context, we develop and analyze a proposal for FT, measurement-free QEC using the nine-qubit Bacon–Shor code. Our simulations confirm that QEC can be performed in a fully FT manner on a linear Rydberg-ion chain despite its limited qubit connectivity. These results establish native multi-qubit Rydberg-ion gates as a valuable resource for fast, high-fidelity quantum computing and highlight their potential for FT QEC.

Recent advances in quantum machine learning have motivated efficient models for sequential data processing. In this paper, we propose Self-Modulating Quantum Fast Weight Programmers, or Self-Modulating QFWP, which extends Quantum Fast Weight Programmers by introducing adaptive modulation over both newly generated fast-weight updates and historical fast-weight memory. Numerical results show that the proposed mechanism improves convergence stability and prediction performance across varying model settings, including different numbers of qubits and input sequence lengths. We further provide theoretical arguments explaining how self-modulation balances new information injection with memory retention, thereby enhancing temporal information propagation. These results suggest that Self-Modulating QFWP is a compact and effective framework for quantum machine learning on time-series data.

Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this paper, we propose a Recursive Quantum Long Short-Term Memory model, or Recursive QLSTM, which extends QLSTM through metacore-based recursive constructions. We numerically test the model under different input sequence lengths, metacore designs, and recursive rules, and identify the best-performing architecture among these variants. For this selected model, we further provide theoretical arguments explaining why its recursive structure improves temporal information propagation and enhances learning performance. Our results suggest that Recursive QLSTM offers a flexible and effective framework for quantum recurrent learning over input time series of various lengths.

Conventional Fabry--Perot interferometry accesses only full braids of anyons and therefore cannot directly probe the elementary \(π\)-rotation exchange. Motivated by the recent quantum-antidot proposal for the Abelian anyons, we propose an interferometry for probing the elementary exchanges of non-abelian anyons using two gate-controlled quantum antidots. By tuning two antidots independently, the device realizes distinct cooperative tunnelling processes, which correspond to different braids of non-abelian anyons. For the unresolved local fusion channels, the difference between the interference signals of the single and double cooperative processes allows us to measure the elementary exchange of the non-abelian anyons, providing a direct probe of their non-abelian statistics and topological spins. For the resolved local fusion channels, the double-cooperative process is further distinguished by a reduced interference amplitude. Our work provides a promising and practical route for manipulating and detecting non-abelian braiding with the fundamental fractional statistics.

Two-dimensional electron systems (2DESs) confined to wide GaAs quantum wells provide a unique platform to study exotic fractional quantum Hall states (FQHSs) because the 2DES has a bilayer charge distribution with significant interlayer tunneling. Precise control over the 2DES density allows the tuning of the interlayer tunneling over a wide range. Here, we present our discovery of new even-denominator FQHSs in the lowest Landau level (orbital index \textit{N} = 0) at filling factors $ν= 3/4$ and 5/4 in an ultrahigh-quality 2DES confined to a 72.5-nm-wide GaAs quantum well. The ground states at $ν= 3/4$ and 5/4 both evolve from composite fermion Fermi seas to FQHSs as the density is raised so that interlayer tunneling is sufficiently reduced and the 2DES becomes two-component, signaled by the behavior of the FQHSs flanking $ν= 3/4$ and 5/4. The two-component nature of the $ν=3/4$ and 5/4 FQHSs is also evident from their extreme sensitivity to the bilayer charge distribution symmetry: both states disappear quickly when the charge distribution is made asymmetric by only $\simeq 2\%$. We find a natural explanation for the 3/4 and 5/4 FQHSs in terms of two states linked by particle-hole symmetry, and using the Scarola-Jain bilayer composite fermion framework which is a generalization of the well-known, two-component, Halperin state ($Ψ_{331}$ state). Our observations elucidate the crucial role of competing energy and length scales in wide quantum wells in stabilizing new ground states.

In the presence of a magnetic field, electronic states of moiré quantum materials develop a Hofstadter spectrum that provides a unique setting for studying the interplay between band topology and strong electron-electron interaction. Using scanning tunneling microscopy, we study Hofstadter's states in bilayer graphene aligned with hexagonal BN and directly visualize the formation of interaction-driven symmetry breaking Chern insulators. Our measurements reveal the formation of phases that double, triple or quadruple the moiré unit cell at fractional filling of the Hofstadter bands, as well as states with complex intra-unit-cell wave functions. We visualize two distinct quantum phenomena in different Chern states, including quantum melting driven by the appearance and proliferation of topological defects, and a quantum transition co-occurring with phase competition and separation.

Understanding particle-induced damage tracks in solid-state materials underpins emerging applications in rare-event detection and quantum defect engineering. Resolving these tracks requires multi-scale readout, from event localization at the millimeter scale to track-morphology reconstruction at the nanoscale. Nitrogen-vacancy (NV) centers in diamond provide such a platform, combining optical localization with quantum sensing of track morphology. Here, we implant sub-MeV carbon ions into nitrogen-rich diamond and detect individual recoil events via spatially localized NV formation. We develop a simulation framework that explains the observed NV yield and predicts that directional information is retained in the NV distribution after annealing. Machine learning further recovers much of the information lost to defect diffusion and limited NV yield, improving head-tail classification to a level comparable to pre-annealed vacancy tracks. Measurements of NV spin coherence indicate compatibility with nanoscale track reconstruction via NV strain mapping and magnetic gradient-based techniques. These results identify promising pathways toward NV-diamond directional detectors for rare events, while the track-modeling framework has broader implications for paleodetection and quantum material synthesis.

Quantum geometry is instrumental in stabilizing exotic phenomena in systems ranging from topological insulators to superconductors. In dispersionless flat bands, where the kinetic energy is quenched, the quantum metric emerges as the fundamental driver of macroscopic collective phenomena. Here, we theoretically demonstrate that lattice-geometry-induced flat bands, such as those in kagome and Lieb lattices, provide a fertile platform for realizing a purely quantum-geometry-driven excitonic insulator (EI) phase. By applying an out-of-plane Zeeman field to lift spin degeneracy without spin-orbit coupling, we establish a Ginzburg-Landau framework in which the electron-hole wavefunction-overlap directly maps the flat-band quantum metric onto the macroscopic free energy. This mapping plays a key role in both the EI and the associated superfluid phases, with the coherence length and phase stiffness emerging directly from the quantum metric. Our analysis reveals that under strong interactions, the quantum metric induces a negative effective kinetic coefficient for the amplitude mode. Rather than destabilizing the uniform condensate, this softens the amplitude fluctuations at a finite momentum, giving rise to a finite-momentum superfluid density fluctuation (FMSDF) state. This state is observable as a periodically modulated magnitude of in-plane magnetization fluctuations. Our findings establish a rigorous link between flat-band quantum geometry and dynamic collective excitonic states, with promising pathways for realization in covalent-organic frameworks (COFs).

The Josephson effect, a hallmark of superconducting phase coherence, drives modern quantum technologies. However, Josephson-based quantum interference has hitherto been tethered to magnetic fields, despite phase coherence being a quintessential, intrinsic trait of superconductivity. Moreover, the Josephson diode effect (JDE) is typically viewed as an anomalous phenomenon indicative of broken symmetries in exotic phases of matter. Here, in planar Josephson junctions made with $\mathrm{Bi}_2\mathrm{O}_2\mathrm{Se}$ and bilayer graphene, we demonstrate that the JDE is a missing universal property of the Josephson effect. Simultaneously, we present an all-electric technology that replaces magnetic flux for controlling and measuring supercurrent interference. Central to our approach is a supercurrent gauge field (SGF), generated and amplified through high-kinetic-inductance superconductors and novel device architectures. By establishing the physical equivalence between the SGF and a magnetic field, we eliminate the reliance on external fields in quantum interference and reveal a universal, field-free JDE mechanism with broad implications for detecting broken-symmetry states. Finally, we show that the SGF offers capabilities beyond those of a conventional magnetic field by experimentally demonstrating a magnetic-free, phase-sensitive technique to construct and characterize finite-momentum superconductivity, opening new frontiers for exploring novel phases of matter and superconducting quantum architectures.

Black phosphorus and its two dimensional counterpart, phosphorene, are typically synthesized through chemical vapor transport using Sn and I2 additives. Chemical vapor deposition synthesis of phosphorene and allotropes is still yet not well understood. Investigating the atomistic mechanisms underlying phosphorus transport and early stage processes is difficult experimentally. In this study, a reactive force field for the PSnI system was developed and applied using ReaxFF based molecular dynamics to explore the early stage phase of the pre nucleation relevant to BP-phosphorene growth. The force field parameters were trained on a comprehensive quantum mechanical dataset covering bond dissociation, angle and torsion profiles, and tin condensed phase equation of state and cluster formation energies, showing strong agreement in both gas and condensed phases. We demonstrate that iodine and density together control phosphorus recombination. Under low density, atomic phosphorus dominates with minimal clustering. Adding I2 greatly increases P-P recombination, promotes the formation of PxIy motifs, and transient SnxPyIz compounds. Higher density systems favor the formation of larger Px clusters and support the development of ternary SnxPyIz compounds that grow by capturing transported phosphorus. At the highest density, the system produces condensed, Hittorf like phosphorus structures at the edges of SnxPyIz clusters, along with BP-like hexagons stabilized by iodine that may act as nucleation seeds. These results offer an atomistic view of transport and early stage steps in BP synthesis and provide a practical reactive model for studying growth conditions and additive effects in BP phosphorene vapor synthesis.

We demonstrate that analysis of the spin polarization of a quantum dot (QD) attached to the topological wire can provide valuable insights into Majorana zero mode (MZM) formation and topological phase transition. Detection is realized by rotation of the Zeeman field in the wire, while retaining the Zeeman field direction in the dot intact. In the presence of Majorana mode, the effective QD spin polarization at Fermi energy changes significantly when the direction of the Zeeman field in the wire changes from parallel to perpendicular to the wire axis. It can be opposed to the wire in its trivial state, when spin polarization remains practically constant while the magnetic field is rotated. Similar unaltered spin polarization is observed when QD spin sub-level at Fermi energy mimics MZM. Moreover, the characteristic non-linear dependence of the spin polarization on the magnetic field magnitude at its critical value identifies a topological phase transition in the wire. This feature is observed independently on the coupling strength of the wire to the dot and the angle of the Zeeman field.

Photonic computing has emerged as a promising platform for accelerating artificial intelligence workloads by enabling low-latency and energy-efficient linear operations such as vector-matrix multiplication. However, scalable on-chip high-order nonlinear processing remains challenging, limiting the functional versatility of current photonic hardware. Here, we present an optoelectronic approach for approximating high-order and high-dimensional nonlinear functions. The key to this approach lies in optical random Fourier feature mapping, which transforms nonlinear function evaluation into an equivalent linear computation. This approach enables nonlinear computing within a linear photonic framework, eliminating the need for complex optical nonlinear or active materials while preserving scalability and computational throughput in a simple silicon photonic circuit. We experimentally demonstrate a broad class of nonlinear functions, including tenth-order Legendre polynomials, computationally demanding special functions (Voigt, Fermi-Dirac, and Fresnel), neural-network activation functions, two-dimensional nonlinear functions, and a 10-dimensional softmax layer. This work establishes a general and scalable strategy for nonlinear computing in photonic integrated hardware and opens a pathway toward fully functional optical accelerators for next-generation computing systems.

We investigate dimensional crossovers in minimal tight-binding models of three-dimensional (3D) topological insulators subject to geometric confinement. While thin films are commonly understood to host a crossover from a 3D strong topological insulator to a two-dimensional (2D) quantum spin Hall phase via hybridization of surface states, we demonstrate that this picture is incomplete once bulk confinement effects and boundary termination are fully taken into account. Using lattice models, we show that reducing the system size induces a strongly non-monotonic dependence of the topology on thickness and microscopic parameters, leading to a sequence of topological phase transitions that is highly sensitive to surface termination. In particular, we find a cascade of dimensional reduction from a 3D topological insulator to a 2D quantum spin Hall phase and ultimately to a one-dimensional phase consisting of end states of Kramers pairs protected by inversion symmetry. Remarkably, we show that both the 2D and 1D topological phases can emerge even when the corresponding 3D bulk phase is topologically trivial. Our results reveal an unexpected universality in the phase diagrams of 3D-to-2D and 2D-to-1D crossovers, pointing toward a unified framework for topology under dimensional reduction.

The precise realization of molecular electronic devices requires a comprehensive understanding of charge transport mechanisms and the specific interplay between electronic and nuclear degrees of freedom. While average current measurements (I-V characteristics) and conventional Inelastic Electron Tunneling Spectroscopy (IETS) offer valuable insights, they are fundamentally limited by temperature-dependent line-width broadening. This study presents a high-resolution spectroscopic methodology utilizing suspended-wire molecular junctions (SWMJs) based on self-assembled monolayers (SAMs) of 1-decanethiol (C10) and 1,1',4',1''-terphenyl-4-thiol (TPT). By systematically probing the voltage-dependent current noise ($ΔI$), we demonstrate that electronic noise spectroscopy circumvents thermal degradation by probing transition rates between vibrational manifolds rather than simple additions of conductance channels, which enables sub-thermal feature mapping. Leveraging a fast-convolution-based Landauer-Büttiker transport model fitted to experimental data, we map complex vibrational manifolds, including high-energy overtones. This allows for the direct extraction of crucial nanoscale molecular parameters, including mode energies, anharmonicities ($x_e$), dissociation energies ($D_e$), and local environment reorganization energies ($E_r$). These parameter-dense noise signatures act as a unique molecular fingerprint, establishing noise spectroscopy as a highly sensitive platform for chemical sensing and discrimination in advanced quantum devices.

We report the fabrication and characterization of an integrated quantum photonic device consisting of an electrically driven whispering-gallery-mode micropillar laser evanescently coupled to a ridge waveguide, both incorporating InGaAs quantum dots (QDs). The lasing characteristics of microlasers are systematically investigated as a function of the pillar-waveguide gap distance. Coherent emission from the whispering-gallery-mode microlaser coupled into the waveguide enables on-chip optical excitation of QDs embedded in an electrically contacted micropillar at the end of the waveguide. Under continuous-wave on-chip excitation, we observe single-photon emission with $g^{(2)}(0) = (3.49 \pm 0.01) \%$ for a QD integrated in the outcoupling micropillar which can be spectrally tuned-by the quantum confined Stark effect. These results constitute an important step toward low-footprint, deterministic, and scalable single-photon sources for QD-based integrated quantum photonic circuits.

The Mpemba effect states that initially hotter systems cool faster than colder ones. While known in convective, conductive, and quantum systems, its radiative analogue is unexplored. Here, this anomaly is realized via phase-change hysteresis of a VO$_2$ nanoparticle near a SiC substrate. After analytically deriving an onset condition, the phase space is mapped. Crucially, latent heat acts as a thermal buffer enabling both ordinary and inverse effects. Near-field coupling governs the relaxation time and enables a passive effect where memory is stored externally via substrate reflection.

The spatial confinement of defect-induced bound states is conventionally governed by the effective mass in dispersive bands. More recently, Compact Localized States (CLSs) arising from exact destructive interference have been utilized to achieve confinement in flat bands. However, CLSs rely on pristine lattice symmetries and fine-tuned defect profiles. The introduction of a generic local impurity inevitably breaks these strict phase-matching conditions, resulting in extensive bound states whose fundamental length scale has remained an open question. Here, we establish a third regime of confinement: the quantum metric bound state. We provide a rigorous mathematical proof demonstrating that in the absence of kinetic energy and CLS protection, the exponential decay length of these states is lower-bounded by the quantum metric of the unperturbed flat band. We demonstrate the tightness of this geometric limit by constructing a family of highly tunable flat-band generators, and we verify its universality across diverse realistic architectures. Ultimately, this classification establishes the independently measurable quantum metric as a predictive design principle for engineering confined modes in synthetic wave platforms.

We derive a gauge-invariant clean-limit decomposition of the second-order dc nonlinear conductivity in multiband tight-binding systems within the velocity-gauge Keldysh Green's function formalism. In the constant-relaxation-time approximation, the dc response separates into four contributions with distinct lifetime $τ$ scalings and physical origins: the nonlinear Drude term $σ^{\mathrm{ND}}_{ijk}\proptoτ^{2}$, the Berry-curvature-dipole term $σ^{\mathrm{BCD}}_{ijk}\proptoτ$, the intraband quantum-metric-dipole term $σ^{\mathrm{intra\text{-}QMD}}_{ijk}\proptoτ^{0}$, and the interband quantum-metric-dipole term $σ^{\mathrm{inter\text{-}QMD}}_{ijk}\proptoτ^{0}$. The intraband term is a Fermi-surface dipole of the ordinary band quantum metric, while the interband term is written, in the present representation, as a Fermi-sea-type response involving a band-normalized quantum metric. Working entirely within the velocity-gauge Keldysh--Kubo framework, we show that all connection-dependent commutator terms generated in the band-basis expansion cancel exactly between the covariant-quantum-connection sector $σ^{\mathcal{C}}_{ijk}$ and the three-Berry-connection sector $σ^{\mathcal{T}}_{ijk}$, making the role of the Peierls contact velocity vertices $V_{ij}$ and $V_{ijk}$ explicit; a complementary projector-based derivation appears in Ulrich et al., Phys. Rev. B 113, L201107 (2026), and our Fermi-surface dc-limit expression agrees with that reference after accounting for index and convention differences. As a diagnostic illustration, we introduce a real two-band model in which the Berry curvature and hence the BCD response vanish identically while the intraband quantum-metric dipole remains finite, establishing a practical route to quantum-metric dc responses not reducible to the Berry-curvature-dipole mechanism.

Abstract Here we review analytical methods for computing the entanglement distribution time in first-generation quantum networks. We describe and briefly discuss the main schemes for entanglement generation, distillation, and swapping, and their combination in repeater chains, providing formulae for mean values and probability functions under a unified framework. We also derive some new expressions that help draw a more comprehensive picture, and present some scheme comparisons for different operational scenarios.

Abstract In conventional photon blockade, the occupation of a cavity mode by more than one photon is suppressed via strong optical nonlinearity. An alternative, called unconventional photon blockade, can occur under weak nonlinearity by relying on quantum interference between fine-tuned cavities. A serious limitation to this approach is the very short antibunching time window, orders of magnitude less than the cavity lifetime. We present a scheme to achieve photon blockade over a large time window of several cavity lifetimes, even exceeding that of conventional photon blockade, while still requiring only weak nonlinearity. This “long-lived photon blockade” (LLPB) occurs when the single-particle Green’s function exhibits a zero at a large cavity loss rate, which is satisfied by an exemplary configuration of four coupled cavities under weak driving. Our analytical results agree well with wavefunction Monte Carlo simulations. The LLPB phenomenon may aid the development of single-photon sources utilizing materials with weak optical nonlinearities.

Carbon nanotubes (CNTs) constitute a highly tunable platform for probing the interplay between structural chirality and quantum transport in quasi-one-dimensional systems. Here, we perform a systematic study of the non-equilibrium orbital response across a broad set of metallic and semiconducting chiral CNTs. We find that the orbital Edelstein susceptibility depends strongly on both chirality and nanotube diameter, revealing that the orbital response cannot be captured by a universal scaling law. Instead, distinct families of CNTs emerge, forming characteristic orbital-response branches uniquely determined by the chiral wrapping vector. We further investigate the role of metallic contacts on orbital-current generation and orbital selectivity. While metallic CNTs rapidly recover their intrinsic orbital response away from the contact region, semiconducting CNTs display pronounced oscillatory behavior arising from interference between transport channels carrying different angular momenta injected by wide-band metallic contacts. Finally, by incorporating angular correlations into the contact self-energy, we demonstrate that chiral CNTs can operate as efficient orbital-angular-momentum filters, selectively transmitting orbitally textured electronic states in accordance with the crystal angular momentum of the propagating bands.

Quantum circuit execution estimates output distributions by repeated measurements, yet developers commonly choose a fixed shot budget before execution. This static choice is brittle: low budgets can under-sample the distribution, while high budgets waste measurements. In this paper, we present StableShots, a black-box online stopping rule for static quantum circuits. The method executes a fixed circuit in small batches, monitors the total-variation distance between cumulative empirical distributions, and stops after repeated evidence of local stability. We evaluate StableShots on 180 QSimBench traces spanning six circuit families, six sizes from 4 to 14 qubits, and five noisy IBM simulated backends. With validation-only calibration and 100 repeated backend-holdout splits, the selected configuration reaches TVD <= 0.05 on all held-out test evaluations with median 7,650 shots, whereas fixed-shot baselines either fail more often or spend substantially more shots.

A theoretical framework is developed for the electron miniband structure in one-dimensional chains of spherical quantum dots subjected to weak positional disorder. Within the tight-binding approximation combined with the effective-medium approach, the stochastic fluctuations of the inter-dot spacing are mapped onto the renormalization of the key Hamiltonian parameters: the hopping integral $ B $, the overlap integral $ Q $, and the on-site energy shift $ M $. Analytical expressions for these disorder-renormalized parameters are derived by performing an ensemble average over a narrow Gaussian distribution of positional deviations ($ σ\ll a $). The resulting generalized dispersion relation shows that weak positional disorder causes a broadening of the minibands. Specifically, for typical fabrication fluctuations $σ= 0.1\,a $, the miniband width increases by 8-12\% (depending on the mean inter-dot distance $a$). At the same time, the sensitivity of the miniband width to disorder decreases rapidly with increasing lattice period due to the exponential decay of the electron wave functions. In the considered weak-disorder regime, the Anderson localization length significantly exceeds the lattice constant, so the miniband states remain delocalized.

Unconventional charge density waves (CDWs) with complex order parameters can host exotic collective modes and non-trivial topologies. They have emerged as a new frontier in the study of quantum matter. Recent experiments on rare-earth tritellurides have reported evidence for a ferroaxial CDW through the detection of characteristic Raman modes. This phase, often regarded as a hidden order, has been recognized to arise from the coupling between charge and orbital degrees of freedom in these materials. Yet, spectroscopic insight into its underlying electronic structure and the explicit form of its order parameter symmetry has remained elusive. Here, we present results from linearly polarized angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM) measurements of the CDW phase in LaTe$_3$. Our ARPES measurements reveal a complex landscape of spectral gaps across the reconstructed Fermi surface, while our STM-based quasiparticle interference (QPI) mapping, enhanced through the selective deposition of atomic scattering centers, directly reveals an inter-orbital CDW with mixed $p_x$-$p_z$ orbital character. The detailed analysis of the QPI characteristics in terms of the order parameter symmetry within the orbital subspace of the Fermi surface suggests a mixed CDW phase with substantial ferroaxial component, which breaks all vertical mirror symmetries. More broadly, our work establishes a powerful spectroscopic pathway, based on scattering off individual atoms, for identifying and characterizing hidden, multi-component electronic orders in quantum materials using STM and ARPES measurements.

Quantum reservoir engineering leverages dissipative processes to achieve desired behaviour, with applications ranging from entanglement generation to quantum error correction. Therein, a structured environment acts as an entropy sink for the system and no time-dependent control over the system is required. We develop a theoretical framework for active reservoir engineering, where time-dependent control over a quantum system is used to manipulate its environment. In this case, the system may act as an entropy sink for the environment. Our framework captures the dynamical interplay between system and environment, and provides an intuitive picture of how finite-size effects and system-environment correlations allow for manipulating the environment by repeated initialisation of the quantum system. We illustrate our results with two examples: a superconducting qubit coupled to an environment of two-level systems and a semiconducting quantum dot coupled to nuclear spins. In both scenarios, we find qualitative agreement with previous experimental results, illustrating how active control can unlock new functionalities in open quantum systems.

We construct an ontological model for the theory known as bilocal classical theory \cite{d2020classicality}. To our knowledge, this is only the second time that an ontological model has been constructed for an entire theory, rather than just for some particular scenarios within a theory. This result refutes a conjecture from \cite{d2020classicality} which suggested that there might be no local-realist ontological model for bilocal classical theory. Moreover, it is the first time that an ontological model has been constructed for a theory that fails to be locally tomographic, showing that the assumption of local tomography underpinning the structure theorem in \cite{schmid2024structuretheorem} is a genuine limitation of the theorem. This demonstrates that in general there is no tension between failures of local tomography and classical explainability (i.e., generalised noncontextuality). In fact, bilocal classical theory is in many ways more simply understood via the underlying ontological model than it is within its original formulation (much as how odd-dimensional stabiliser subtheories can be more simply understood via Spekkens&amp;apos; toy theory). Furthermore, this result naturally leads to the question, does every locally-classical theory admit of an ontological model? By constructing a concrete counterexample, we show that this is not the case. Our findings demonstrate that there is no straightforward relationship between theories being locally-classical, and them being classically-explainable. This shows that the fundamental status of compositional properties (such as local tomography) is not a technical side-issue, but a central and unavoidable question for a coherent understanding even of classicality itself.

The problem of deciding whether a set of quantum measurements is jointly measurable is known to be equivalent to determining whether a quantum assemblage is unsteerable. This problem can be formulated as a semidefinite program (SDP). However, the number of variables and constraints in such a formulation grows exponentially with the number of measurements, rendering it intractable for large measurement sets. In this work, we circumvent this problem by transforming the SDP into a hierarchy of linear programs that compute upper and lower bounds on the incompatibility robustness with a complexity that grows polynomially in the number of measurements. The hierarchy is guaranteed to converge and it can be applied to arbitrary measurements – including non-projective POVMs (Positive Operator-Valued Measures) – in arbitrary dimensions. While convergence becomes impractical in high dimensions, in the case of qubits our method reliably provides accurate upper and lower bounds for the incompatibility robustness of sets with several hundred measurements in a short time using a standard laptop. We also apply our methods to qutrits, obtaining non-trivial upper and lower bounds in scenarios that are otherwise intractable using the standard SDP approach, although such bounds are significantly looser than the ones obtained in the qubit case. Finally, we show how our methods can be used to construct local hidden state models for states (i.e., to prove that a state cannot lead to steering under any possible local measurements), or conversely, to certify that a given state exhibits steering; for two-qubit quantum states, our approach is comparable to, and in some cases outperforms, the current best methods.

Abstract Quantum communication protocols require efficient detection schemes to maximize the information transfer rate between the sender and the receiver. To this aim, we have demonstrated that weak-field receivers, merging wave-like and particle-like features, can be considered as a valid alternative to already existing receivers, such as optical homodyne detection. To better emphasize the potential of our receiver, in this work we consider a proof of concept for quaternary communication based on coherent states with the same amplitude and different phase values. We show that the encoding in phase requires a fine control of phase noise, which is obtained through a feedback system. The results achieved in terms of mutual information and secret key generation rate encourage further increase of the alphabet towards an approximately continuous phase modulation.

Abstract Integrating quantum key distribution (QKD) into optical networks is a crucial step toward the adoption of quantum technologies in existing telecommunication fiber infrastructures. However, state-of-the-art solutions face significant challenges, including sensitivity to classical noise, particularly spontaneous Raman scattering, limited transmission distances, and varying network conditions. In this work, we present a novel discrete-variable QKD system running a time-bin BB84 protocol operating in the O-band (1295.56 nm), where the impact of dominant noise sources is effectively reduced. Combined with passive narrow-spectral filtering at the receiver, our system demonstrates robustness across diverse dense wavelength-division multiplexing scenarios, making it practical for real-world deployments. We validate its performance through extensive testing, showing stable key generation coexisting with different classical traffic conditions up to 17 dBm of total launch power. These results represent a significant advancement toward the integration of QKD into existing fiber networks, paving the way for secure quantum communication on a large scale.

Abstract A rotating surface can induce a frequency shift in incident light by changing its angular momentum, a phenomenon known as the rotational Doppler effect (RDE). This effect provides a means to estimate the angular velocity of the rotating surface. In this work, we develop a continuous-variable quantum protocol for estimating the angular velocity of a rotating surface via the RDE. Our approach exploits squeezed and displaced Laguerre–Gaussian modes as quantum resources, which interact with a rotating metallic disc with surface roughness. The frequency shift induced by the RDE is then measured using a homodyne detection scheme. By analyzing the Fisher information, we demonstrate that the proposed squeezing-enhanced protocol achieves Heisenberg scaling in the ideal noiseless regime. Furthermore, we investigate the influence of noise and consider different surface models to assess their impact on the protocol’s performance. While Heisenberg scaling is degraded in the presence of noise, we show that optimizing the energy allocation ratio between displacement and squeezing of the probe ensures that the quantum strategy consistently outperforms its classical counterpart.

Abstract We review how to use von Neumann’s measurement procedure to estimate a phase, using an efficient Hamiltonian simulation subroutine acts on a block-encoded Hamiltonian. We show that the resulting algorithm can be used to solve quantum phase estimation (QPE) or quantum energy estimation (QEE) with competitive complexity scaling. We then use recent results for block-encoding implementations to derive the Clifford + T complexity bound for QPE with respect to model-relevant parameters of the Hamiltonian and the desired precision. With this result, we demonstrate an efficient algorithm for QEE beginning from any linear combinations of Pauli strings. In this way, we argue that a well-understood and long-standing idea retains practical legitimacy for fault-tolerant era algorithms, once the costs of Hamiltonian simulation are accounted for.

Abstract The generation of high-purity, coherent qubits is essential for quantum technologies. Free electron wavepackets are a promising platform, but their development into qubits has been hindered by the multi-level sideband structure generated in standard laser-electron interactions. Here, we overcome this fundamental limitation by demonstrating the distillation of a pristine flying electron qubit with over 99% purity from such a multi-level state. Through a sequence of coherent laser modulations, we engineer quantum interference to distill the electron state, coherently suppressing all except two energy sidebands and confining the population to a genuine two-level system. We further demonstrate coherent control of the relative population and phase, enabling balanced coherent superpositions that are valuable for quantum interference applications. Our work establishes distillation as a general route to realize pristine flying-electron qubits encoded in discrete momentum states.

Abstract Micromachined vapor cells have revolutionized chip-scale quantum sensors, including magnetometers and atomic clocks. In parallel, Rydberg-atom quantum sensing has emerged as a powerful platform for broadband, non-invasive and ultra-sensitive electrometry, enabling compact atom-based antenna elements for electromagnetic reception, often referred to as quantum antennas. Yet, to date, Rydberg sensing has largely been limited to glass-blown, cm-scale vapor cells. Here, we perform Rydberg spectroscopy and electrometry using a wafer-scale-fabricated Pyrex–Si–Pyrex cell with millimeter-scale dimensions. The Rydberg spectroscopic line is characterized with respect to critical parameters such as temperature, the frequency and amplitude of the applied radio frequency (RF) field, light intensity, and the spatial position of the interrogating beam. Our study reveals lineshapes directly influenced by a complex landscape of electrostatic fields with values up to approximately 0.6 V cm − 1 . By controlling key parameters, we were able to reduce the effect of these internal electric fields, and demonstrate the detection of RF fields assessed using the Autler–Townes splitting with a minimum detectable field of 20 μ V cm − 1 . Our results highlight the potential of micromachined vapor cells for subwavelength electromagnetic field measurements, with applications in communications, near-field RF imaging, and chip-scale quantum technologies.

Abstract Photons are promising candidates for quantum information technology due to their high robustness and long coherence time at room temperature. Inspired by recent advances in photonic computing techniques, research has increasingly turned to quantum machine learning (QML) on photonic platforms. Although photons provide a high-dimensional quantum feature space suitable for computation, a general understanding of how photon number can be harnessed for learning tasks remains limited. Here, we establish both theoretically and experimentally a learning-capacity advantage of multi-photon states over single-photon states in photonic QML. We prove that the learning capacity of linear optical circuits, quantified by the rank of the data quantum Fisher information matrix, scales polynomially with the photon number. This scaling enables multi-photon models to generalize from fewer training states than corresponding single-photon models and to achieve lower test loss under the same architecture and learning protocol. Moreover, we experimentally corroborate these findings through unitary learning and metric learning tasks, by performing online training on a fully programmable photonic integrated platform. Our work highlights the potential of photonic QML and paves the way for achieving quantum enhancement in practical machine learning applications.

Fermions with opposite spins occupying half-filled conjugate Chern bands exhibit interaction physics distinct from their multi-component Landau-level counterparts with the same chirality. This is largely due to unavoidable inter-species collisions that preclude the Halperin-type wavefunctions available in multi-component Landau levels. In this work, we propose and evaluate a variational wavefunction for a fractional quantum spin Hall state with Z_4 topological order in a pair of conjugate Landau levels. This Z_4 topological order has previously been shown to be the minimal topological order compatible with charge conservation, $S_z$ conservation, time-reversal symmetry, and the fractional spin Hall conductance 1/2 suggested by previous twisted MoTe$_2$ experiments. Our construction is based on the condensation of an anyonic exciton formed by the neutral fermionic excitations in a decoupled pair of Moore-Read Pfaffian state and its conjugate. By coupling the chiral and anti-chiral Ising conformal field theories associated with the two spin species, we introduce a variational mass parameter in the Z_4 trial wavefunction that captures the inter-spin-species s-wave pairing of composite fermions alongside the intra-spin-species p-wave pairing. We assess the energetics of this trial state using Monte Carlo sampling on a spherical geometry. Because the coupled state intrinsically involves Landau-level mixing, we explicitly evaluate the resulting kinetic energy penalty. Our phase diagram reveals that the proposed Z_4 state becomes energetically favorable in a sizable region of parameter space, over both the decoupled pair of conjugate Pfaffian states and an alternative exciton condensate state. These results provide a concrete microscopic wavefunction realization of this Z_4 fractional quantum spin Hall phase, and propose a route to constructing additional families of such states.

Quantum geometry has emerged as a unifying concept across condensed matter physics, underlying phenomena from nonlinear topological response to flat-band superconductivity. While usually formulated within band theory, quantum geometry remains meaningful in disordered interacting systems~\cite{resta1999electron}. Here we show that the first negative moment of the optical conductivity -- proportional to the zero temperature quantum Fisher information as a bound on the multipartite entanglement -- provides an experimental probe of quantum geometry across the three-dimensional metal-insulator quantum phase transition in phosphorus-doped silicon. We extract a quantum geometric length $\ell$ that characterizes the local wavefunctions. Far from the transition, this length is almost coincident with the Bohr radius of the hydrogenic phosphorus donors, reflecting their atomic-scale quantum geometry. Approaching the transition, $\ell$ is enhanced, but does not diverge continuously like a correlation length; it jumps discontinuously to infinity at the critical point. This reflects the UV domination of the sum rule in three dimensions that renders it insensitive to the critical fluctuations driving the diverging dielectric constant and correlation length. Its enhancement demonstrates a ``puffing" of the donor polarizability volume of quantum geometric origin, which yields a quantum geometric corrected Clausius-Mossotti description in closer agreement with the diverging dielectric response and provides a quantum mechanical foundation for the century-old Herzfeld metallization criterion.

We investigate the dividing line between classical and quantum computational power in estimating properties of matrix functions. More precisely, we study the computational complexity of two primitive problems: given a function f and a Hermitian matrix A , we compute a matrix element of f ( A ) or a local measurement on f ( A ) | 0 ⟩ ⊗ n , with | 0 ⟩ ⊗ n being an n -qubit reference state vector, in both cases up to additive approximation error. We consider four functions—monomials, Chebyshev polynomials, the time evolution function, and the inverse function—and probe the complexity across a broad landscape covering different problem input regimes. Namely, we consider two types of matrix inputs (sparse and Pauli access), matrix properties (norm and sparsity), the approximation error, and function-specific parameters. We identify BQP- forms of both problems for each function and then toggle the problem parameters to easier regimes to see where hardness remains, or where the problem becomes classically easy. As part of our results, we make concrete a hierarchy of hardness across the functions; in parameter regimes where we have classically efficient algorithms for monomials, all three other functions remain robustly BQP-, or hard under usual computational complexity assumptions. In identifying classically easy regimes, among others, we show that for any polynomial of degree poly ( n ) , both problems can be efficiently classically simulated when A has O ( log  n ) nonzero coefficients in the Pauli basis. This contrasts with the fact that the problems are BQP- in the sparse access model even for constant row sparsity, whereas the stated Pauli access efficiently constructs sparse access with row sparsity O ( log  n ) . Our work provides a catalog of efficient quantum and classical algorithms for fundamental linear-algebra tasks.

The unrivaled maturity of its nanofabrication makes silicon a promising hardware platform for quantum information processing. To this end, efficient single-photon sources and spin-photon interfaces have been implemented by integrating color centers or erbium dopants into nanophotonic resonators. However, the optical emission frequencies in this approach are subject to temporal fluctuations on both long and short timescales, which hinder the development of quantum applications. Here, we investigate this limitation and demonstrate that it can be alleviated by integrating the emitters into Fabry-Perot instead of nanophotonic resonators. Their larger optical mode volume enables both increasing the distance to crystal surfaces and operating at a lower dopant concentration, which reduces implantation-induced crystal damage and interactions between emitters. As a result, we observe a fivefold reduction of the spectral diffusion linewidth down to 4.0(2) MHz. Calculations and experimental investigations of isotopically purified 28 Si crystals suggest that the remaining spectral instability is caused by laser-induced electric field fluctuations. In direct comparison with a nanophotonic device, the instability is significantly reduced at the same intracavity power, enabling a tenfold increase of the optical coherence time up to T 2 = 20 ( 1 ) μ s . These findings represent a key step toward spectrally stable spin-photon interfaces in silicon and their potential applications in quantum networking and distributed quantum information processing.

Abstract The accurate characterization of quantum systems is essential for the advancement of quantum technologies. In particular, certifying convex functions of quantum states plays a central role in many applications. We present a certification method for experimentally prepared quantum states that accounts for both shot noise and measurement imperfections in the data-acquisition stage. Building upon previous work, our method extends confidence regions to accommodate imperfect control over measurements. The values of the functions can then be bounded using convex optimization techniques. We provide explicit prescriptions for quantifying the noise contribution from finite statistics and for estimating the effect of measurement imperfections. By jointly incorporating statistical and systematic errors, the method yields a robust certification framework for quantum experiments.

Abstract Leveraging the intrinsic probabilistic nature of quantum systems, generative quantum machine learning (QML) offers the potential to outperform classical learning models. Current generative QML algorithms mostly rely on general-purpose models that, while being very expressive, face several training challenges. One potential way to address these setbacks is by constructing problem-informed models that are capable of more efficient training on structured problems. In particular, probabilistic graphical models provide a flexible framework for representing structure in generative learning problems and can thus be exploited to incorporate inductive bias into QML algorithms. In this work, we propose a problem-informed quantum circuit Born machine Ansatz for learning the joint probability distribution of random variables, with independence relations efficiently represented by a Markov network (MN). We further demonstrate the applicability of the MN framework in constructing generative learning benchmarks and compare our model’s performance to previous designs, showing that it outperforms problem-agnostic circuits. Based on a preliminary analysis of trainability, we narrow down the class of MNs to those exhibiting favourable trainability properties. Finally, we discuss the potential of our model to offer quantum advantage in the context of generative learning, and present a practical scenario demonstrating the scalability of the approach.

Abstract Generalized bicycle codes (GB codes) represent a promising family of quantum low-density parity-check codes, characterized by high code rates and relatively local qubit connectivity. A subclass of the GB code called bivariate bicycle codes (BB codes) has garnered significant interest due to its compatibility with two-layer connectivity architectures on superconducting quantum processors. However, one key limitation of BB codes is the high qubit connectivity degree requirements (degree 6), which exacerbates the noise susceptibility of the system. Building on the recent progress in implementing multiple two-qubit gates on a single chip, this work introduces Louvre—a routing-based framework designed to reduce qubit connectivity requirements in GB codes. Specifically, Louvre-7 achieves degree reduction while preserving the depth of the syndrome extraction circuit, whereas Louvre-8 further minimizes the connectivity by slightly increasing the circuit depth. When applied to BB codes, these two schemes could reduce the average degree to 4.5 and 4, respectively. Crucially, Louvre eliminates some of the long-range, error-prone connections, which is a distinct advantage over prior approaches. Numerical simulations demonstrate that Louvre-7 has an logical error rate indistinguishable from that of the standard syndrome extraction circuits of GB codes, while Louvre-8 only incurs a slight error rate penalty.

We introduce QFT$\rightarrow$FFT, a family of HPC FFT libraries that compute the discrete Fourier transform by executing a quantum Fourier transform (QFT) circuit on classical quantum computer simulators. Input arrays are mapped directly to state amplitudes with explicit normalization/indexing, making QFT a drop-in replacement for FFT primitives. A backend-agnostic planner builds a fused-gate schedule and memory layout adapters to increase arithmetic intensity and reduce memory data movement. We implement this design on top of Google's C++ \texttt{qsim} and evaluate OpenMP, AVX, and CUDA backends. On an AMD EPYC Zen2 processor, our AVX performance is on par with that of multithreaded FFTW, utilizing 64 threads. On an NVIDIA A100, the CUDA backend achieves more than $4\times$ lower time than both AVX and FFTW on AMD EPYC Zen2 at larger sizes. We also employ an approximate QFT (AQFT) that truncates small-angle controlled rotations beyond a cutoff $k$, reducing circuit depth and runtime while preserving accuracy.

Atom-like emitters in solids have emerged as promising platforms for quantum sensing and information processing. Among the major challenges are inhomogeneities in emitter fine structure, which complicates quantum control. Here, we introduce a framework that leverages this emitter diversity to simplify the experimental resources needed to create optically heralded spin cluster states across N q emitters from the conventional order O ( N q ) to O ( 1 ) within ensembles of N q ∼ 10 – 100 . Specifically, the optimized pulse sequence simultaneously corrects parameter variations (pulse-length error and frequency detuning error), achieving single-qubit gate fidelities exceeding 99.99% for errors (normalized relative to Rabi-drive strength) up to 0.3, while maintaining fidelities above 99% even for errors as large as 0.4. Applying this optimized pulse sequence in the form of a Carr-Purcell-Meiboom-Gill (CPMG) based dynamical decoupling protocol to the dominant noise spectral density of silicon-vacancy centers in diamond, our approach enhances ensemble-average coherence times by more than a factor of 7 relative to interleaved bang-bang-based CPMG. For state-of-the-art dilution refrigeration systems, we further estimate sharply reduced heating when driving a global resonant optimal dynamical decoupling across N q silicon-vacancy spins, potentially resolving the current trade-off between spin coherence and scaling to N q ≫ 1 . We further introduce a modified single-photon entanglement protocol with an efficient algorithm for deterministic entanglement compilation. Depending on the decoupling window, our method yields order O ( 10 2 – 10 4 ) more entanglement links than bang-bang sequences, with theoretical guarantees of order Ω ( N q ) unique links—improvable via control-parameter tuning. Our approach thus offers enhanced fidelity, scalability, and robustness. Together, these techniques provide foundational tools—including global unitary control, phase denoising, remote entanglement, and compilation—for scalable quantum computing architectures based on heterogeneous spin ensembles.

Topological data analysis (TDA) aims to extract noise-robust features from a dataset by examining the number and persistence of holes in its topology. We provide an efficient quantum algorithm for a computational problem closely related to a core task in TDA—determining whether a given hole persists across different length scales. Further, we prove the problem itself is B Q P 1 -hard, implying that a classical solution is extremely unlikely; this stands in contrast to all previous quantum approaches to TDA, where the problems were also intractable for quantum computers, or where a rigorous proof of classical hardness still remains open. This result implies an exponential quantum speedup for this problem under standard complexity-theoretic assumptions. Our approach relies on encoding the persistence of a hole in a variant of the guided sparse Hamiltonian problem, where the guiding state is constructed from a harmonic representative of the hole.

Abstract Imaginary time evolution (ITE) is a well-established method for ground-state preparation, a fundamental problem in many fields such as materials science, chemistry, and optimization. Quantum ITE (QITE) approximates this evolution on quantum hardware but suffers from high circuit depth and numerous measurements. In this work we introduce adaptive-time compressed QITE (ACQ), a novel algorithm that reduces resource-cost by combining adaptive time steps with circuit compression. This approach leverages geometric insights by characterizing its relationship to geodesic trajectories with a measure that distinguishes trajectories in CP N . Recalling that ITE is a gradient flow on the complex projective plane CP N , such trajectory measures allow one to measure the deviation from geodesicity of said flow. For Hamiltonians with only two distinct eigenvalues (spectral cardiality), ITE and QITE exactly trace geodesics, this fact motivates an adaptive strategy for systems whose corresponding spectral cardinality is greater than 2, where QITE unitaries are reused until an energy increase signals departure from the ITE path. This is implemented via a line search for energy minimization. Circuit compression is achieved by approximating the sequence of QITE unitaries with a single element of a one-parameter group. Numerical simulations on the transverse field Ising model and the Heisenberg model demonstrate that ACQ achieves comparable fidelity to standard QITE while significantly reducing the number of QITE optimizations and maintaining fixed circuit depth during propagation. Gate-count estimates and an analysis of the fidelity scaling with truncation parameters are provided. A gate count and performance comparison with the state of the art method double bracket QITE is also performed.

Abstract Continuous-time quantum hardware implementations generally lack the native capability to implement high-order terms that would facilitate efficient compilation of quantum algorithms. This limitation has, in part, motivated the development of perturbative gadgets—multi-qubit constructions used to effect a desired Hamiltonian using engineered low-energy subspaces of a larger system constructed using simpler, usually two-body, primitives. In this work, we demonstrate how a class of non-perturbative gadgets can produce high-order multi-body interactions by taking advantage of the odd–even properties of topological defect subspaces. The simplest example uses domain-wall defects in an effective Ising spin chain with linear connectivity and three-body couplings, alongside three- or five-body driving terms depending on the intended use. We demonstrate a version of a gadget which can perform an encoded bit-flip operation on a minor embedding chain, an important task to mitigate the limitations of quasi-two-dimensional (also sometimes called quasi-planar) topology. Although this will be the main focus of the paper due to conceptual simplicity, there exist systems constructed with only two-body couplings where the boundaries determine whether there are an odd or even number of defects, namely ice-like systems which may yield more complex gadget-like constructions.

AWS and QuEra will bring the first fault-tolerant quantum computers to the cloud, enabling scientifically relevant applications starting in 2028. Since launching Amazon Braket in 2020, AWS has provided customers access to quantum computing hardware across multiple modalities, helping them explore quantum algorithms and prepare for the future of accelerated computing. Today, we are announcing an expanded strategic collaboration with QuEra Computing to bring Libra, the first fault-tolerant quantum computer capable of tackling scientifically relevant problems to Amazon Braket customers. At AWS, we view quantum computing as a foundational compute modality. In the fullness of time, we envision quantum processors becoming a natural part of the AWS compute portfolio, alongside CPUs, GPUs, and AI/ML accelerators. Another tool in the toolbox our customers can rely on to accelerate production workloads and tackle problems out of reach for traditional compute options today. QuEra has been a key quantum hardware provider to AWS since we started our quantum computing journey in 2019. In 2022, together we launched Aquila, a 256-qubit analog Rydberg device, built for scientific exploration. And over the past years, our customers in industry and academia have been pushing the boundaries of what we thought possible, driving innovation in quantum reservoir computing , high-energy physics simulations , and quantum algorithms for financial optimization . Since we launched Aquila, neutral-atom quantum computing has matured rapidly. QuEra and affiliated academic partners at Harvard and MIT have demonstrated all the key ingredients for large-scale quantum error correction in a series of landmark experiments (e.g. 1. A fault-tolerant neutral-atom architecture for universal quantum computation , 2. Logical quantum processor based on reconfigurable atom arrays , 3. Experimental demonstration of logical magic state distillation , and 4. Continuous operation of a coherent 3,000-qubit system ).

Phase estimation, due to Kitaev \cite{Kit95}, is one of the most fundamental subroutines in quantum computing. In the basic scenario, one is given black-box access to a unitary U , and an eigenstate &amp;#x007C; &amp;#x03C8; &amp;#x27E9; of U with unknown eigenvalue e i &amp;#x03B8; , and the task is to estimate the eigenphase &amp;#x03B8; within &amp;#x00B1; &amp;#x03B4; , with high probability. The cost of an algorithm for us is the number of applications of U and U &amp;#x2212; 1 .We tightly characterize the cost of several variants of phase estimation where we are no longer given an eigenstate, but are required to estimate the maximum eigenphase of U , aided by advice in the form of states (or a unitary preparing those states) which are promised to have at least a certain overlap &amp;#x03B3; with the top eigenspace.We give algorithms and nearly matching lower bounds for all ranges of parameters.We show that a small number of copies of the advice state (or of an advice-preparing unitary) are not significantly better than having no advice at all. We also show that having lots of advice (applications of the advice-preparing unitary) does not significantly reduce cost, and neither does knowledge of the eigenbasis of U . We immediately obtain a lower bound on the complexity of the Unitary recurrence time problem, resolving an open question of She and Yuen \cite{SY23}.Lastly, we study how efficiently one can reduce the error probability in the basic phase-estimation scenario. We show that a phase-estimation algorithm with precision &amp;#x03B4; and error probability &amp;#x03F5; has cost &amp;#x03A9; ( 1 &amp;#x03B4; log &amp;#x2061; 1 &amp;#x03F5; ) , matching an easy upper bound. This contrasts with some other scenarios in quantum computing (e.g., search) where error-probability reduction costs only a factor O ( log &amp;#x2061; ( 1 / &amp;#x03F5; ) ) . Our lower bound uses a variant of the polynomial method with trigonometric polynomials.

Nonlocality is an essential concept that distinguishes quantum from classical models and has been extensively studied in systems of qubits. For higher-dimensional systems, certain results for their two-level counterpart, like Bell violations with stabilizer states and Clifford operators, do not generalize. On the other hand, similar to continuous variable systems, Wigner negativity is necessary for nonlocality in qudit systems. We propose a new generalization of the CHSH inequality for qudits by inquiring correlations related to the Wigner negativity of stabilizer states under the adjoint action of a generalization of the qubit &amp;#x03C0; / 8 -gate. A specified stabilizer state maximally violates the inequality among all qudit states based on its Wigner negativity. The Bell operator not only serves as a measure for the singlet fraction but also quantifies the volume of Wigner negativity. Additionally, we show how a bipartite entangled qudit state can serve as a witness for contextuality when it exhibits Wigner negativity. Furthermore, we identify rational-phase diagonal unitaries as the key resource that exactly reproduce the CGLMP and SATWAP violation with the maximally entangled state through simple phase-difference alignment.

This work investigates whether quantum walks on simplicial complexes exhibit quantum advantages. We introduce a novel quantum walk that encodes the combinatorial Laplacian, a key object reflecting the topology of the simplicial complex. We construct a unitary encoding projecting onto the kernel of the Laplacian, representing the harmonic cycles in the complex's homology. Our efficient construction of quantum walk unitaries for clique complexes paves the way for exploring higher-order interactions within topological structures. Our construction requires O ( n 3 log &amp;#x2061; ( 1 / &amp;#x03F5; ) / &amp;#x03BB; k ) gates, where n is the number of vertices, &amp;#x03BB; k is the smallest non-zero eigenvalue of the Laplacian, and &amp;#x03F5; is the projection error. Our results indicate apparent superpolynomial quantum speedup with quantum walks, without quantum oracles, provided the spectral gap of the Laplacian is inverse-polynomially bounded and efficient simplex sampling is available.Crucially, the walk operates on a state space encompassing both positively and negatively oriented simplices, effectively doubling its size compared to unoriented approaches. Through coherent interference of these paired simplices, we are able to successfully encode the combinatorial Laplacian, which would otherwise be impossible. This is our major technical contribution. We also extend the framework by constructing variant quantum walks that enable us to: (1) estimate normalized persistent Betti numbers throughout a deformation process, (2) verify a specific QMA 1 -hard problem related to clique complex homology, showcasing potential applications in computational complexity theory, and (3) solve the high-dimensional discrete Dirichlet problem (HDDP), generalizing the classical discrete Dirichlet problem on graphs to simplicial complexes, with an apparent superpolynomial speedup over the best known classical algorithm.

Simulations of quantum systems with Hamiltonian classical stochastic noise can be challenging when the noise exhibits temporal correlations over a multitude of time scales, such as for 1 / f noise in solid-state quantum information processors. Here we present an approach for simulating Hamiltonian classical stochastic noise that performs temporal coarse-graining by effectively integrating out the high-frequency components of the noise. We focus on the case where the stochastic noise can be expressed as a sum of Ornstein-Uhlenbeck processes. Temporal coarse-graining is then achieved by conditioning the stochastic process on a coarse realization of the noise, expressing the conditioned stochastic process in terms of a sum of smooth, deterministic functions and bridge processes with boundaries fixed at zero, and performing the ensemble average over the bridge processes. For Ornstein-Uhlenbeck processes, the deterministic components capture all dependence on the coarse realization, and the stochastic bridge processes are not only independent but taken from the same distribution with correlators that can be expressed analytically, allowing the associated noise propagators to be precomputed once for all simulations. This combination of noise trajectories on a coarse time grid and ensemble averaging over bridge processes has practical advantages, such as a simple concatenation rule, that we highlight with numerical examples.

We introduce a non-equilibrium version of the Caldeira-Leggett model in which a quantum particle is strongly coupled to a set of engineered reservoirs. The reservoirs are composed by collections of squeezed and displaced thermal modes, in contrast to the standard case in which the modes are assumed to be at equilibrium. The model proves to be very versatile. Strongly displaced/squeezed reservoirs can be used to generate an effective time dependence in the system Hamiltonian and can be identified as sources of pure work. In the case of squeezing, the time dependence is stochastic and breaks the fluctuation-dissipation relation, this can be reconciled with the second law of thermodynamics by correctly accounting for the energy used to generate the initial non-equilibrium conditions. To go beyond the average description and compute the full heat statistics, we treat squeezing and displacement as generalized Hamiltonians on a modified Keldysh contour. As an application of this technique, we show the quantum-classical correspondence between the heat statistics in the non-equilibrium Caldeira-Leggett model and the statistics of a classical Langevin particle under the action of squeezed and displaced colored noises. Finally, we discuss thermodynamic symmetries of the heat generating function, proving a fluctuation theorem for the energy balance and showing that the conservation of energy at the trajectory level emerges in the classical limit.

Complex optical design is hindered by conventional piecewise setup, which prevents modularization and therefore abstraction of subsystems at the circuit level. This limits multiple fields that require complex optics systems, including quantum computing with atoms and trapped ions, because their optical systems are not scalable. We present an open-source Python library for optical layout (PyOpticL) which uses beam-path simulation and dynamic beam-path routing for quick and easy optical layout by placing optical elements along the beam path without a priori specification, enabling adaptive, path-based layouts with automatic routing and connectivity. We use PyOpticL to create modular `drop-in&amp;apos; optical baseplates for common optical subsystems used in atomic and molecular optics (AMO) experiments including laser sources, frequency and intensity modulation, and locking to an atomic reference for stabilization. We demonstrate this minimal working example of a dynamic full laser system for strontium trapped ions by using it for laser cooling, qubit state detection, and over 99% fidelity single-qubit gates with 3D printed baseplates. This enables a new paradigm of design abstraction layers for engineering optical systems leveraging modular baseplates, as they can be used for any wavelength in the system and enables scaling up the underlying optical systems for quantum computers. This new open-source hardware and software code-to-CAD library seeks to foster open-source collaborative hardware and systems design across numerous fields of research including AMO physics and quantum computing with neutral atoms and trapped ions.

The advancement and scaling of quantum technology has made the learning and identification of quantum systems and devices in highly multidimensional parameter spaces a pressing task for a variety of applications. In many cases, the integration of real-time feedback control and adaptive choice of measurement settings places strict demands on the speed of this task. Here we present a joint model selection and parameter estimation algorithm that is fast and operable on a large number of model parameters. The algorithm is based on variational Bayesian inference, which approximates the target posterior distribution by optimizing a tractable family of distributions, making it more scalable than exact inference methods relying on sampling and that generally suffer from high variance and computational cost in high-dimensional spaces. We show how a regularizing prior can be used to select between competing models, each comprising a different number of parameters, identifying the simplest model that explains the experimental data. The regularization can further separate the degrees of freedom, e.g., quantum systems in the environment or processes, which contribute to major features in the observed dynamics, with respect to others featuring small coupling, which only contribute to a background. As an application of the introduced framework, we consider the problem of the identification of multiple individual nuclear spins with a single electron spin quantum sensor, relevant for nanoscale nuclear magnetic resonance and for the implementation of multiqubit quantum networking nodes. With the number of environmental spins unknown a priori, our Bayesian approach is able to correctly identify the model, i.e., the number of spins and their couplings. We benchmark the algorithm on both simulated and experimental data, using standard figures of merit, and demonstrate that we can estimate dozens of parameters within minutes. Our methodology is compatible with the implementation of real-time adaptive choice of experimental settings in multiparameter estimation, which has the potential to greatly decrease the estimation time in a variety of metrology, tomography, and characterization tasks by prioritizing the measurements with the highest content of information.

This perspective outlines promising pathways and critical obstacles on the road to developing useful quantum computing applications, drawing on insights from the Google Quantum AI team. We propose a five-stage framework for this process, spanning from theoretical explorations of quantum advantage to the practicalities of compilation and resource estimation. For each stage, we discuss key trends, milestones, and inherent scientific and sociological impediments. We argue that two central stages—identifying concrete problem instances expected to exhibit quantum advantage, and connecting such problems to real-world use cases—represent essential and currently under-resourced challenges. Throughout, we touch upon related topics, including the promise of generative artificial intelligence for aspects of this research, criteria for compelling demonstrations of quantum advantage, and the future of compilation as we enter the era of early fault-tolerant quantum computing.

Abstract Quantum Darwinism explains how tenets of classical reality, such as objectivity and repeatability, emerge within a quantum Universe. As a mathematical framework, quantum Darwinism also provides guiding principles that determine what physical models support emergent classical behavior, what specific observables obey classical laws, and much more. Recently, we demonstrated that in the regime where a quantum model exhibits quantum Darwinism, the Kirkwood–Dirac quasiprobability distributions for all disjoint multiparty measurement protocols become effectively classical. In the present work, we use this connection as a tool to study how the breaking of quantum Darwinism in a specific model translates to non-classical measurement statistics. Interestingly, this provides effective tools for benchmarking the genuine quantum characteristics of NISQ hardware, which we demonstrate with IonQ’s trapped-ion and IBM’s superconducting quantum computing platforms.

Quantum algorithms require repeated circuit executions, known as shots, to estimate output distributions accurately. Determining the minimal number of shots needed to meet a target accuracy is crucial to reduce costs and resource usage, especially on today's noisy and expensive quantum hardware. In this paper, we address the shot optimisation problem in a black-box setting, where no assumptions are made about the structure of the quantum circuit or the noise model of the backend. We introduce IncrementalExecution, a novel online framework that dynamically determines when to stop executing shots based on the principle of point of diminishing returns: the point at which additional shots no longer significantly alter the empirical distribution of a fixed circuit. The framework supports customisable policies for shot management, enabling flexible trade-offs between execution cost and result fidelity within static execution scenarios. We assess our proposal through an extensive experimental evaluation spanning 33,750 framework configurations across 180 unique static quantum circuit-backend combinations, for a total of 7.3M independent experiments. Unlike prior work that relies on problem-specific knowledge or algorithm-dependent assumptions (e.g., variational or adaptive workflows), our approach is applicable to a large set of static circuits and immediately deployable on current quantum cloud platforms.

The development of quantum networks faces a key challenge: the contradiction between probabilistic long-range entanglement generation and finite coherence time. Existing routing protocols typically focus on global state computation or path optimization. As the network scales up, classical delays accumulate and exacerbate decoherence, leading to a decrease in entanglement fidelity. To reduce routing decision delays to levels far below the coherence time of qubits, we propose a protocol based on local measurement and classical feedforward. This protocol reduces the local decision complexity to amortized O(1) level, ensuring that the decision delay is always much smaller than the coherence time of qubits. We map this protocol onto a dual-species trapped-ion platform and perform hybrid simulations. The results show that the proposed protocol performs well in terms of both resource efficiency and time feasibility. Noise analysis indicates that readout fidelity is the main bottleneck of this protocol, but noise suppression can be achieved by employing an erasure transformation in the dual-species architecture, combined with spatial multiplexing and branch independence, thereby ensuring the generation of high-fidelity star subgraphs. This protocol provides a clear path to achieving high-fidelity star subgraphs. These subgraphs can serve as general modules, merging to construct arbitrary subgraphs, providing a feasible solution for future fault-tolerant distributed quantum computing.

Quantum computing promises transformative advances across science and industry, yet the physical hardware that enables these computations remains invisible to the public: quantum processors operate inside sealed dilution refrigerators at temperatures near absolute zero, making direct observation impossible. This "imagination gap" between quantum computing's growing societal impact and the public's ability to visualize it represents a significant barrier to quantum literacy and workforce development. We present Quantum Cinema, an open-source, browser-based interactive application that closes this gap by transforming invisible quantum hardware into explorable, cinematic experiences using generative world models. Quantum Cinema guides users through a four-act narrative -- from the foundational Nobel Prize-winning science of quantum entanglement, through curated video introductions to three major quantum computing architectures (trapped-ion, neutral-atom, and superconducting systems), into immersive three-dimensional generative worlds that make invisible quantum phenomena observable, and finally to interactive radar-chart comparisons grounded in real quantum device specifications. All three-dimensional environments are generated using WorldLabs' generative world model platform and are scientifically grounded in curated metrics from Amazon Web Services (AWS) Braket quantum hardware. Quantum Cinema requires no installation, no specialized hardware, and no quantum computing background. It is designed to serve two distinct communities: scholars and developers seeking to replicate or extend the platform, and educators, researchers, and science communicators seeking an intuitive tool for explaining quantum hardware to diverse audiences. This paper describes the system architecture, the generative world model pipeline, use cases for both communities, and directions for future work.

Building upon Wan, Zhong (2025) \cite{wan2025cuttingstabiliserdecompositionsmagic} we present a few methods on how to simulate the non-Clifford d = 5 magic state cultivation circuits\cite{gidney2024magicstatecultivationgrowing} with a sum of &amp;#x2248; 8 Clifford ZX-diagrams on average, at 0.1 &amp;#x0025; noise. Compared to a magic cat state stabiliser decomposition of all 53 non-Clifford spiders ( 6,377,292 terms required), this is more than 7 &amp;#x00D7; 10 5 times reduction in the number of terms. Our stabiliser decomposition has the advantage of representing the final non-Clifford state (in light of circuit errors) as a sum of Clifford ZX-diagrams. This will be useful in simulating the escape stage of magic state cultivation, where one needs to port the resultant state of cultivation into a larger Clifford circuit with many more qubits. Still, it's necessary to only track &amp;#x2248; 8 Clifford terms. Our result sheds light on the simulability of operationally relevant, high T -count quantum circuits with some internal structure.Finally, we provide numerical results for full non-Clifford stabiliser rank simulation based on t s i m along with optimisations using our cutting decompositions. Nearly 4 &amp;#x00D7; 10 6 shots per second can be obtained on a laptop for the smaller d = 3 circuits at uniform circuit level noise p = 0.0005 , making it only &amp;#x223C; 1.1 times slower than its (circuit-unspecific and un-optimised) fully Clifford proxy simulation via s t i m using S gates.

Recent advances in analog and digital quantum-simulation platforms have enabled exploration of the spectrum of entanglement Hamiltonians via variational algorithms. In this work we analyze the convergence properties of the variationally obtained solutions and compare them to numerically exact calculations in quantum critical systems. We demonstrate that interpreting the cost functional as an integral permits the deployment of iterative quadrature schemes, thereby reducing the required number of measurements by more than an order of magnitude even in the presence of noise. We further show that a modified ansatz captures deviations from the Bisognano-Wichmann form in lattice models, improves convergence, improves trainability and provides a cost-function-level diagnostic for quantum phase transitions. Finally, we establish that a low cost value does not by itself guarantee convergence in trace distance. Nevertheless, it faithfully reproduces degeneracies and spectral gaps, which are essential for applications to topological phases.

Quantum linear optics without post-selection is not powerful enough to produce any quantum state from a given input state. This limits its utility since some applications require entangled resources that are difficult to prepare. Thus, a deeper understanding of linear optical state preparation is needed. In this work, we give a recipe to derive conserved quantities in the evolution of arbitrary states along any possible passive linear interferometer. One example of such an invariant is the spectrum of a density matrix mapped onto the Lie algebra of passive linear optical Hamiltonians. These invariants give necessary conditions for exact state preparation: if the input and output states have different invariants, it is impossible to design a passive linear interferometer that evolves one into the other. Moreover, we provide a lower bound to the distance between an output and target state based on the distance between their invariants. This gives a necessary condition for approximate or heralded state preparations. Therefore, the invariants allow us to narrow the search when trying to prepare useful entangled states, like NOON states, from easy-to-prepare states, like Fock states. We conclude that future exact and approximate state preparation methods will need to consider the necessary conditions given by our invariants to weed out impossible linear optical evolutions.

Understanding the capabilities of classical simulation methods is key to identifying where quantum computers are advantageous. Not only does this ensure that quantum computers are used only where necessary, but also one can potentially identify subroutines that can be offloaded onto a classical device. In this work, we show that it is always possible to generate a of a subregion (dubbed a “patch”) of an expectation landscape produced by a parameterized quantum circuit. That is, we provide a quantum-enhanced classical algorithm which, after simple measurements on a quantum device, allows one to classically simulate approximate expectation values of a subregion of a landscape. We provide time and sample complexity guarantees for a range of families of circuits of interest, and further numerically demonstrate our simulation algorithms on an exactly verifiable simulation of a Hamiltonian variational and long-time dynamics simulation on a 127-qubit heavy-hex topology.

Arrays of neutral atoms present a promising system for quantum computing, quantum sensors, and other applications, several of which would profit from the ability to load, cool, and image the atoms in a finite magnetic field. In this work, we develop a technique to image and prepare 87 Rb atom arrays in a finite magnetic field by combining electromagnetically induced transparency cooling with fluorescence imaging. We achieve an average readout fidelity of 99.7 ( 1 ) % at 98.2 ( 3 ) % survival probability and up to 68 ( 2 ) % single-atom stochastic loading probability in a 2.3 G magnetic field, with performance validated at fields up to 10 G. We further develop a model to predict the survival probability, which also agrees well with several other atom-array experiments. Our technique cools both the axial and radial directions, and will enable future continuously operated neutral-atom quantum processors and quantum sensors.

Abstract Classical shallow networks are universal approximators. Given a sufficient number of neurons, they can reproduce any continuous function to arbitrary precision, with a resource cost that scales linearly in both the input size and the number of trainable parameters. In this work, we present a quantum optical protocol that implements a shallow network with an arbitrary number of neurons. Both the input data and the parameters are encoded into single-photon states. Leveraging the Hong–Ou–Mandel effect, the network output is determined by the coincidence rates measured when the photons interfere at a beam splitter, with multiple neurons prepared as a mixture of single-photon states. Remarkably, once trained, our model requires constant optical resources regardless of the number of input features and neurons.

Abstract Quantum state transfer (QST) is a fundamental requirement for scalable quantum computation, where fast and reliable communication between distant subsystems is essential. In this work, we present a protocol for QST in linear Ising chains. Starting from a perfect state transfer scheme via a Heisenberg Hamiltonian with inhomogeneous couplings, we adapt it for architectures implementing the transverse-field Ising model by encoding the information in domain walls. The resulting linear Ising chain makes quantum transport experiments accessible to many platforms for analog quantum simulation. We test the protocol for 1-, 2-, and 3- spin states, obtaining high transfer fidelities of up to 0.99 and study the accuracy dependence on the domain wall approximation. These results are the first step in paving the way for an experimental implementation of the protocol.

Device-independent quantum information is attracting significant attention, particularly for its applications in information security. This interest arises because the security of device-independent protocols relies solely on the observed outcomes of spatially separated measurements and the validity of quantum physics. Sequential scenarios, i.e., where measurements occur in a precise temporal order, have been proved to enhance performance of device-independent protocols in some specific cases by enabling the reuse of the same quantum state. In this work, we propose a systematic approach to designing sequential quantum protocols for device-independent security. Our method begins with a bipartite self-testing qubit protocol and transforms it into a sequential protocol by replacing one measurement with its non-projective counterpart and adding an additional user thereafter. We analytically prove that, with this systematic construction, the resulting ideal correlations are secure in the sense that they cannot be reproduced as a statistical mixture of other correlations, thereby enabling, for example, the device-independent certification of all the randomness present in the observed correlations. The general recipe we provide can be exploited for further development of new device-independent quantum schemes for security.

Rydberg–cavity systems are emerging as promising platforms for quantum simulation and quantum information processing. These hybrid architectures combine two complementary interaction mechanisms: cavity photons mediate collective long-range couplings, while Rydberg excitations generate strong short-range interactions. Together, they offer a setting for engineering many-body phases characterized by a hierarchy of interactions across widely different length scales. In this work, we introduce a minimal and scalable model for such systems. Focusing on the strong Rydberg blockade regime, we restrict the Hilbert space to the subspace enforced by the blockade, yielding a kinetically constrained long-range model in one spatial dimension. This approach both captures the physics of Rydberg–cavity experiments in the regime of strong Rydberg interactions and provides a conceptually transparent framework for studying the interplay of long-range and short-range interactions. At equilibrium, in addition to paramagnetic and Néel-ordered phases, the system supports a blockaded ferromagnetic/superradiant phase, distinct from the conventional superradiant phase. Out of equilibrium, we identify long-range quantum many-body scars, which are atypical nonthermal eigenstates that evade the eigenstate thermalization hypothesis, and giving rise to slow entanglement growth. In contrast to the linear-in-time entanglement growth characteristic of short-range scarred models, these long-range scars exhibit logarithmic entanglement dynamics. Our results establish a minimal yet versatile framework for Rydberg–cavity systems, and provide a stepping stone for future theoretical and experimental studies of this frontier platform in quantum many-body physics.

Abstract Superconducting resonators integrated with germanium (Ge) quantum wells (QWs) offer a promising platform for hybrid quantum devices. Yet, in the most common heterostructure architectures, they have so far been limited by sizable photon losses. Here, we report the fabrication and characterization of microwave resonators patterned in the aluminum (Al) thin film of an in-situ grown superconductor/semiconductor hybrid heterostructure (HS). The semiconductor part of this hybrid HS is grown on a commercial Ge substrate. We consistently achieve internal quality factors Q i &gt; 1000, surpassing previous results on Ge QW heterostructures grown using the concept of a virtual Ge substrate on silicon (Si) substrates. We reach Q i ≈ 49,000 at single-photon occupation and a plateau of Q i ≈ 20,000 at sub-one photon, an order of magnitude larger than any previously reported value of resonators on Ge QW structures at low power. We further characterize the thin Al film forming the resonator, extracting its kinetic inductance and superconducting gap, and studying its magnetic field dependence. Notably, the resonance remains well-defined up to in-plane magnetic fields of 850 mT. A hysteresis emerges in the out-of-plane magnetic field dependence, for both the resonance frequency and the quality factor, indicating an interesting interplay between vortex-and quasiparticle loss mechanisms.

Quantum circuit routing is a key step in compiling programs for noisy intermediate-scale quantum processors, particularly superconducting devices whose sparse fixed coupling makes routing a central compilation cost. Routes that appear efficient by standard overhead metrics such as SWAP count, routed two-qubit count, and depth can still lose fidelity when they pass through poorly calibrated couplers. We study a calibration-aware graph reinforcement-learning router that uses same-day calibration data from superconducting IBM Heron r2 processors to choose hardware-edge SWAPs. We train the policy with proximal policy optimization and evaluate it with exact simulated fidelity across nine Munich Quantum Toolkit (MQT) Bench circuits and three calibration snapshots. Across these evaluations, pooled mean exact fidelity is 0.727, compared with 0.440 for SWAP-based bidirectional heuristic search (SABRE)-best20 and 0.481 for target-aware SABRE. We observe that fidelity gains come with higher routed two-qubit counts and are concentrated in 5 qubit and 8 qubit circuit families; under the fixed tree action graph, all 10 qubit families favor SABRE-best20. Overall, our results show that calibration-aware learned routing can improve fidelity beyond gate-count-driven compilation, by roughly 0.25 to 0.29 in absolute mean fidelity over the SABRE-family baselines.

Classical simulation of quantum circuits plays a crucial role in validating quantum hardware and delineating the boundaries of quantum advantage. Among the most effective simulation techniques are those based on the stabilizer extent, which quantifies the overhead of representing non-Clifford operations as linear combinations of Clifford unitaries. However, finding optimal decompositions rapidly becomes intractable as it constitutes a superexponentially large optimization problem. In this work, we exploit symmetries in the computation of the stabilizer extent, proving that for real, diagonal, and real-diagonal unitaries, the optimization can be restricted to the corresponding subgroups of the Clifford group without loss of optimality. This “strong symmetry reduction” drastically reduces computational cost, enabling optimal decompositions of unitaries on up to seven qubits using a standard laptop—far beyond previous two-qubit limits. Additionally, we employ a “weak symmetry reduction” method that leverages additional invariances to shrink the search space further. Applying these results, we demonstrate exponential runtime improvements in classical simulations of quantum Fourier transform circuits and measurement-based quantum computations on the Union Jack lattice, as well as insights into the nonstabilizer properties of multicontrolled phase gates and unitaries generating hypergraph states. Our findings establish symmetry exploitation as a powerful route to scale classical simulation techniques and deepen the resource-theoretic understanding of quantum advantage.

Abstract Predicting the performance of a Quantum Neural Network (QNN) on a given dataset before its training can save critical resources. However, obtaining such a priori information is, in general, very challenging. The Quantum Neural Tangent Kernel (QNTK) has recently emerged as a tool to mathematically describe the behavior of QNNs. Here, we provide practical guidelines for using the QNTK to diagnose the performance of a given QNN model. In particular, we link QNTK spectral features to the training dynamics, and we show how a first-order kernel approximation can predict the expected inference performance. By analyzing the interplay between the number of model parameters and of training samples, we identify a mismatch at the interpolation threshold: while the QNTK exhibits a double descent in generalization error, we observe that QNNs do not show this behavior in practice. This suggests that QNTK diagnostics are mostly reliable for overparametrized models well above the interpolation regime. Extensive numerical simulations across different architectures and datasets validate our approach. Our results demonstrate that QNTK diagnostics yields useful information about QNN behavior for sufficiently deep circuits, and enable detecting and addressing potential shortcomings in model design.

Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approximation parameters -- such as bond dimension thresholds -- remains a costly trial-and-error process. We present a family-aware neural architecture that predicts both the minimum approximation threshold required to achieve target fidelity and the expected wall-clock runtime for quantum circuit simulation, given only the circuit's OpenQASM description and execution context. Our key insight is that quantum circuits from different algorithmic families (e.g., QFT, Grover, VQE) exhibit fundamentally distinct simulation cost profiles due to their differing entanglement structures. We employ family-conditioned residual corrections -- additive, family-specific adjustments atop a shared backbone, drawing on established conditional computation techniques -- enabling the model to capture both universal circuit properties and algorithmic nuances. The architecture incorporates a pretrained family classifier (97.5% accuracy) and domain-informed algorithm fingerprint features derived from gate-composition heuristics. Evaluated on circuits spanning 7--130 qubits across 10 algorithm families, our system achieves 79.5% exact threshold accuracy (91.2% within one rung) and $R^2 = 0.82$ runtime correlation, with inference completing in approximately 50 ms -- replacing trial-and-error simulation runs that may take minutes to hours. Ablation studies confirm that family-aware modeling provides the single largest performance improvement (+3.2 percentage points), validating the hypothesis that algorithm family is a first-class feature for simulation cost prediction.

We study superspace concentration as a quantum resource, formalized through the focus measure F(\r{ho}) = λ_max(\r{ho}_super) - the largest eigenvalue of the reduced superspace state - which quantifies the capacity of a quantum system to concentrate informational weight into a preferred subspace of an extended degree-of-freedom space. We develop a complete resource-theoretic framework around this measure and validate its properties through GPU-accelerated numerical simulation. Analytic decoherence predictions are confirmed to machine precision (1.11 x 10^{-16}) for superspace dimensions dS in {2,4,8,16,32}. Focus monotonicity holds across 10,000 random states with zero violations under four focus-non-generating channels across six system configurations. Focused quantum states resist coherent unitary attacks with significantly greater resilience than standard fidelity predicts, with focus remaining above 0.9 at attack strength ε = 0.302 versus ε = 0.174 for fidelity. We further demonstrate that the focus measure and the U(dS)-asymmetry measure are operationally distinct: asymmetry remains near zero and provides no robustness signal under coherent and targeted attacks while focus tracks spectral concentration and remains robust until ε > 0.3. The connection between Grover's algorithm and superspace concentration is made explicit via the identity F(|ψ_k><ψ_k|) = P(marked), providing a resource-theoretic interpretation of oracle query complexity. Finally, we provide the first numerical characterization of the focus capacity gap ΔF, identifying a log_2(dS) scaling law confirmed for both product and correlated noise channels.

This post was contributed by Lingnan Shen, Mao Lin, Cedric Yen-Yu Lin, Di Xiao, and Ting Cao Quantum computing is beginning to simulate forms of matter that are difficult to study in the lab or compute classically. In this work, researchers from University of Washington and Amazon Braket demonstrate one such milestone. They realized a fundamentally new quantum state—the fermionic Laughlin state—on a programmable quantum processor. Topological phases of matter underpin some of the most exotic phenomena in condensed matter physics. They offer deep insights into the fundamental laws of nature such as the emergence of fractionally charged excitations and enable next-generation computing paradigms through robust, fault-tolerant quantum computation. Yet probing these phases in real materials remains extraordinarily difficult due to the stringent conditions required for topological order to emerge. This has motivated the use of programmable quantum processors to simulate and manipulate exotic topological states in a controlled setting. Among topological states, the Laughlin state embodies fractionalization, anyonic excitations, and incompressibility—hallmarks of the fractional quantum Hall (FQH) effect. These properties make the Laughlin state a cornerstone for understanding exotic quantum matter, while also informing the broader scientific roadmap toward topological approaches to quantum computing. While the bosonic analogs of Laughlin states have been realized on photonic and cold-atom platforms, a genuine fermionic Laughlin state had not previously been demonstrated on a digital quantum processor. In this post, researchers describe how they realized the ν = 1/3 fermionic Laughlin state on IonQ’s trapped-ion quantum computers, accessed through Amazon Braket. The approach uses an efficient and scalable Hamiltonian Variational Ansatz (HVA) [1]. We demonstrate an end-to-end workflow—from Hamiltonian design and ansatz construction to error mitigation and observable extractio

We present an end-to-end algorithmic pipeline where a noisy digital quantum computer is used to approximate the value of the Jones polynomial at the fifth root of unity for any input link, i.e., a closed braid. This problem is DQC1-complete for Markov-closed braids and BQP-complete for Plat-closed braids, and we accommodate both versions of the problem. Even though it is widely believed that DQC1 is strictly contained in BQP, and so is “less quantum,” the resource requirements of classical algorithms for the DQC1 version are at least as high as for the BQP version, and so we potentially gain “more advantage” by focusing on Markov-closed braids in our exposition. We demonstrate our quantum algorithm on Quantinuum’s H2-2 quantum computer and show the effect of problem-tailored error-mitigation techniques. Further, leveraging that the Jones polynomial is a link invariant, we construct an efficiently verifiable benchmark to characterize the effect of noise present in a given quantum processor. In parallel, we develop and benchmark the state-of-the-art tensor-network-based classical algorithms for computing the Jones polynomial. The reconfigurable tools provided in this work allow for precise resource estimation to identify minimum link sizes for near-term quantum advantage in practice for a meaningful quantum-native problem in knot theory, if a candidate set of links are provided.

Abstract We address the task of verifying whether a quantum computer, designed to be protected by a specific stabilizer code, correctly encodes the corresponding logical qubits. To achieve this, we develop a general framework for subspace verification and explore several practically significant stabilizer code subspaces. First, we present two efficient verification strategies for general stabilizer code subspaces, using measurements of their stabilizer generators and stabilizer groups, respectively. Then, building on the observation that certain tests can be conducted in parallel due to specific structural properties of the subspace, we propose a coloring strategy tailored to graph code subspaces and an XZ strategy for Calderbank–Shor–Steane code subspaces. Compared to stabilizer-based strategies, these new strategies require significantly fewer measurement settings and consume fewer state copies, achieving near-global optimality. Notably, all the strategies employ a limited number of Pauli measurements, are non-adaptive, and work for mixed states, enabling efficient experimental certification of whether quantum states remain within the target code subspace in noisy quantum computers. This work presents the first systematic study of efficient verification of stabilizer code subspaces with local measurements.

Abstract Quantum neural networks (QNNs) are widely used as trainable models for solving variational problems, where their ability to represent complex functions directly determines performance. However, accurately quantifying this expressivity remains a major challenge, limiting the understanding of the expressive power of QNNs. Here, we introduce the effective rank κ as a quantitative measure of expressivity. We show that the expressivity of a QNN is determined by the interplay of three factors: the dataset, the measurement operators, and the circuit structure. Unlike conventional metrics based on parameter sampling or entanglement structure, κ captures the number of independent parameters that effectively contribute to the model output, providing an operational and data-dependent characterization of expressivity while avoiding costly parameter sampling. We demonstrate that κ can reach its theoretical maximum 4 n − 1 for an n -qubit system when the circuit architecture, input distribution, and measurement protocol are jointly optimized. Leveraging this insight, we employ κ as a design objective within a reinforcement learning framework with a self-attention transformer agent to automatically discover highly expressive circuit architectures. Our results show that the proposed approach efficiently identifies high-performing circuit configurations, outperforming heuristic designs and random search in terms of sample efficiency. By bridging theoretical characterization with automated design, our approach provides a practical, scalable, and computationally efficient route for constructing expressive quantum circuits, advancing the development of quantum machine learning models.

Abstract Fault-tolerant quantum computers must be designed in conjunction with classical co-processors that decode quantum error correction measurement information in real-time. In this work, we introduce the belief propagation plus ordered Tanner forest (BP + OTF) algorithm as an almost-linear time decoder for quantum low-density parity-check codes. The OTF post-processing stage removes qubits from the decoding graph until it has a tree-like structure. Provided that the resultant loop-free OTF graph supports a subset of qubits that can generate the syndrome, BP decoding is then guaranteed to converge. To enhance performance under circuit-level noise, we introduce a technique for sparsifying detector error models. This method uses a transfer matrix to map soft information from the full detector graph to the sparsified graph, preserving critical error propagation information from the syndrome extraction circuit. Our BP+OTF implementation first applies standard BP to the full detector graph, followed by BP + OTF post-processing on the sparsified graph. Numerical simulations show that the BP+OTF decoder achieves similar logical error suppression compared to state-of-the-art inversion-based and matching decoders for bivariate bicycle and surface codes, respectively, while maintaining almost-linear runtime complexity across all stages.

We analyze the task of estimating a multi-parameter unitary belonging to the S U ( 2 ) or S U ( 1 , 1 ) groups, in a two-bosonic-mode scenario and investigate the scaling of the precision in terms of the total particle number. For the S U ( 2 ) case, the total particle number is conserved by the evolution and we discuss optimal states in fixed- n subspaces, identifying eigenstates of J z 2 as useful resources, even allowing simultaneous Heisenberg precision scaling for all three parameters. In the S U ( 1 , 1 ) case instead, the conserved quantity is the particle number difference between the two modes, and we identify useful probe states in the sector with an equal number of particles in the two modes. These states are analogous to the S U ( 2 ) case and would also allow simultaneous Heisenberg precision scaling for all three parameters.We then consider the more pragmatic scenario of an estimation via expectation values of time-evolved observables, which we restrict to be the first two moments of the generators. We analyze the maximal precision achievable in this setting and we find that the twin-Fock state emerges in both the S U ( 2 ) and the S U ( 1 , 1 ) cases as the only one potentially allowing Heisenberg scaling for the estimation of two out of the three parameters. As a complement, we also consider other probe states with fluctuating number of particles, with measurements restricted to quadratic expressions in the mode operators. In this scenario, simultaneous Heisenberg scaling in multiple parameters seems mostly forbidden, with the only exception being an input two-mode squeezed state for the estimation of a two-parameter S U ( 2 ) . This extends to the multiparameter scenario the well-established intuition that the performance of a S U ( 2 ) interferometer can be enhanced by a prior S U ( 1 , 1 ) operation.

Recent work highlighted the importance of higher-order correlations in quantum dynamics for a deeper understanding of quantum chaos and thermalization. The full Eigenstate Thermalization Hypothesis, the framework encompassing correlations, can be formalized using the language of Free Probability theory. In this context, chaotic dynamics at long times are proposed to lead to free independence or "freeness" of observables. In this work, we investigate these issues in a paradigmatic semiclassical model – the kicked top – which exhibits a transition from integrability to chaos. Despite its simplicity, we identify several non-trivial features. By numerically studying 2n-point out-of-time-order correlators, we show that in the fully chaotic regime, long-time freeness is reached exponentially fast. These considerations lead us to introduce a large deviation theory for freeness that enables us to define and analyze the associated time scale. The numerical results confirm the existence of a hierarchy of different time scales, indicating a multifractal approach to freeness in this model. Our findings provide novel insights into the long-time behavior of chaotic dynamics and may have broader implications for the study of many-body quantum dynamics.

Entanglement witnesses (EWs) are a collection of observables that can characterize separable states and, experimentally, estimating EWs can verify entangled states. In this work, we show that a fixed measurement setting on a multipartite entangled state, which we introduce as a network state for the purpose, can estimate EWs. Namely, entangled states can be fully verified in a measurement-based manner, in which experimenters do not necessarily change measurement settings. We present a fixed measurement setting and network states for estimating decomposable EWs, equivalent to the partial transpose criteria. We also consider non-decomposable EWs that detect bound entangled states beyond the partial transpose criteria. The results can be extended to multipartite states such as graph states, a resource for measurement-based quantum computing, and readily applied to distributed settings such as quantum metrology or sensor networks where multipartite entangled states are resourceful.

Classical shadows provide a versatile framework for estimating many properties of quantum states from repeated, randomly chosen measurements without requiring full quantum state tomography. When prior information is available, such as knowledge of symmetries of states and operators, this knowledge can be exploited to significantly improve sample efficiency. In this work, we develop three classical shadow protocols for Z 2 lattice gauge theory, where a dual formulation enables a rigorous analysis of resource requirements, including both circuit depth and sample complexity. Our approaches can offer exponential improvements in sample complexity over symmetry-agnostic methods, albeit at the cost of increased circuit complexity. While our analysis is restricted to Z 2 lattice gauge theory, our approach offers a blueprint for similar protocols for more general lattice gauge theory models which are currently at the forefront of quantum simulation efforts.

The study of quantum reference frames has received renewed interest over the last years, leading to the parallel development of non-equivalent frameworks by different communities. We clarify the differences between these frameworks. At the mathematical level, they mainly differ in the kind of symmetry (either weak or strong) employed to constrain the system. We show that this mathematical difference corresponds to a fundamental physical question: whether the global charge associated to the symmetry group is accessible to symmetry-constrained observers. In this context, we formulate a definition of a perspective in terms of operational capacities, or lack thereof. Turning to consequences of adopting either approach, we discuss how adopting the weak approach induces an ambiguity in the momenta included in each perspective and bars from defining reversible QRF transformations. We then review and analyze the existing arguments motivating each approach, and show how they bear upon the problem of charge accessibility. Finally, we introduce a simple operational scenario in which upholding two reasonable physical postulates leads to the conclusion that internal observers could measure the global charge by 1/ performing a relativized interference measurement and 2/ classically communicating.

Quantum phenomena offer the possibility of measuring physical quantities with precision beyond classical limits. However, current progress is constrained by scalability, environmental noise, and challenges in practical integration. This highlights the necessity for novel approaches. An emerging paradigm in this direction is , which harnesses the enhanced susceptibility and nonclassical correlations that naturally occur near quantum phase transitions as resources for quantum-enhanced precision. This tutorial provides a pedagogical introduction to key concepts and a detailed overview of prominent quantum sensing strategies that exploit critical phenomena in metrology. Through examples of increasing complexity, the reader is guided through various critical quantum sensing protocols applied to different critical systems. Special emphasis is placed on the optimal scaling of estimation precision with respect to fundamental resources. Finally, we discuss how critical quantum metrology extends from idealized models to realistic open-system, dissipative regimes, and strongly correlated fermionic systems, outlining both the challenges and opportunities for future quantum technologies.

Multiqubit gates that involve three or more qubits are usually thought to be of little significance for fault-tolerant quantum error correction because single gate faults can lead to errors of high Pauli weight. However, recent works have shown that multiqubit gates can be beneficial for measurement-free fault-tolerant quantum error correction and for fault-tolerant stabilizer readout in unrotated surface codes. In this work, we investigate multiqubit Rydberg gates that are useful for fault-tolerant quantum error correction in single-species neutral-atom platforms and can be implemented with global laser pulses that do not individually address atomic sites. We develop an open-source Python package to generate analytical, few-parameter pulses that implement the desired gates while minimizing gate errors due to Rydberg-state decay. The tool also allows us to identify parameter-optimal pulses, characterized by a minimal parameter count for the pulse ansatz. Measurement-free quantum error correction protocols require controlled-controlled-Z (CCZ) gates, which we analyze for atoms arranged in symmetric and asymmetric configurations. We investigate the performance of these schemes for various single-, two-, and three-qubit gate error rates, showing that break-even performance of measurement-free quantum error correction is within reach of current hardware. Moreover, we study Floquet quantum error correction protocols that comprise two-body stabilizer measurements. Those can be realized using global three-qubit gates, and we show that this can lead to a significant reduction in shuttling operations. Simulations with realistic circuit-level noise indicate that applying three-qubit gates for stabilizer measurements in Floquet codes can yield competitive logical qubit performance in experimentally relevant error regimes.

Abstract Scalable quantum networks require high-quality multi-wavelength light sources to enable simultaneous quantum communication among multiple users 1 . However, realizing such sources with high brightness, low noise, and chip-scale integration remains challenging. We demonstrate a high-quality and multi-wavelength quantum light source based on a periodically poled thin-film lithium niobate (TFLN) microring resonator employing spontaneous parametric down-conversion (SPDC) with a 100-GHz free spectral range (FSR), compatible with International Telecommunication Union (ITU) Channel Grid. In our experiment, twelve pairs of non-degenerate photon pairs are generated, exhibiting a photon-pair generation rate (PGR) of 817 MHz/mW, brightness of 1.86 × 10 9 Hz/mW 2 /GHz, and a coincidence-to-accidental ratio (CAR) of 51,829 ± 2204. The source enables predictable single photons with g (2) (0) = 0.015 ± 0.006 and energy-time entanglement with 99.5% raw visibility. Operating at room temperature, telecom wavelengths, and compatible with network channels, this work represents a crucial step toward realistic scalable, integrated quantum photonic networks in the future.

Quantum reinforcement learning (QRL) is a promising approach to learn effective decision strategies across several applications with stochastic environments. Instead of directly modeling the random variables that govern these environments, existing QRL architectures indirectly approximate environment behavior by estimating expected outcomes, which limits their expressive power and adaptive potential. Overcoming such challenges requires a novel QRL approach that exploits the distributional nature of quantum computers to directly model environment random variables as quantum state distributions. Hence, in this paper, a novel framework dubbed quantum-native reinforcement learning (QnRL) is proposed. QnRL is a distributional RL framework that learns conditional distributions naturally in Hilbert space via superimposed and entangled quantum states. Thus, QnRL can directly model the behavior of stochastic learning environments via the natural properties of quantum systems. QnRL accomplishes this via a novel, proposed quantum amplitude kickback (QuAK) algorithm that enables comparing the $n$-th power of the $m$-th moment of multiple superimposed distributions. It is theoretically proven that a conditional action policy distribution is distilled from the moments of a quantum generative model entirely within Hilbert space via QuAK, and optimized via QnRL. This complex distribution composition is also shown to provide extra dimensions for expressing environment correlations that are unknown to purely classical and classically-sampled quantum distributional models. Experimental results across diverse environments show that QnRL achieves up to $82.9\%$ higher evaluation scores, with up to $94.3\%$ fewer parameters on average, more accurately estimates the expected return for unseen observations, and better adapts to varying stochastic conditions compared to the baseline.

The power of quantum random number generation is more than just the ability to create truly random numbers—it can also enable , which allows the user to verify the implementation integrity of critical quantum components with minimal assumptions. In this work, we develop and implement a self-testing quantum random number generator (QRNG) chipset capable of generating 15.33 Mbits of certifiable randomness in each run, producing an expansion rate of 5.11 × 10 − 4 at a repetition rate of 10 MHz, with quantum side information considered for a high level of security. The chip design is based on a highly loss-and-noise-tolerant measurement-device-independent protocol, where random coherent states encoded using quadrature phase shift keying are used to self-test the integrated homodyne detectors—well-known to be challenging to characterize in practice. Importantly, this proposal opens up the possibility of implementing miniaturized self-testing QRNG devices at production scale using standard silicon photonics foundry platforms.

Recent studies of monitored quantum dynamics have revealed that projective measurements, traditionally viewed as decohering operations, can instead generate and sustain long-range entanglement. Motivated by these, we ask how many physical qubits must be measured in random basis to irreversibly destroy quantum information encoded in a quantum error-correcting code. We study this problem for a broad class of stabilizer and subsystem codes, derive necessary and sufficient conditions for measurement-induced information destruction, and show that many codes, including concatenated and topological codes, achieve the maximal measurement threshold p m th = 1 , meaning that the encoded information survives as long as arbitrarily small but finite fraction of physical qubits remain unmeasured. Beyond this surprising robustness, we find a structural relation underlying maximal thresholds. Namely, we prove that if the Pauli basis of the logical operator measured at full measurement does not concentrate on a single Pauli, then the measurement threshold always satisfies p m th = 1 . This result uncovers a structural relation between logical measurement statistics and stability under partial measurement, revealing a general mechanism by which access to measurement outcomes enhances decodability under monitored dynamics.

Abstract In quantum information, asymmetry, i.e. the lack of symmetry, is a resource allowing one to accomplish certain tasks that are otherwise impossible. Similarly, in a Bell test using any given Bell inequality, the maximum violation achievable using quantum strategies respecting or disregarding a certain symmetry can be different. In this work, we focus on the symmetry involved in the exchange of parties and explore when we have to trade this symmetry for a lower-dimensional quantum strategy in achieving the maximal violation of given Bell inequalities. For the family of symmetric Collins-Gisin-Linden-Massar-Popescu inequalities, we provide evidence showing that there is no such trade-off. However, for several other Bell inequalities with a small number of dichotomic measurement settings, we show that symmetric quantum strategies in the minimal Hilbert space dimension can only lead to a suboptimal Bell violation. In other words, there exist symmetric Bell inequalities that can only be maximally violated by asymmetric quantum strategies of minimal dimension. In contrast, one can also find examples of asymmetric Bell inequalities that are maximally violated by symmetric correlations. The implications of these findings on the geometry of the set of quantum correlations and the possibility of performing self-testing therefrom are briefly discussed.

Abstract Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Quantum software bugs often yield silent, incorrect outputs rather than explicit errors, making them particularly difficult to detect and repair with conventional techniques. Although large language models (LLMs) have shown strong performance on classical software engineering tasks, their ability to debug quantum code remains largely unexplored. To bridge this gap, we propose QBugLM, a multi-agent framework that automates the quantum software debugging pipeline, from taxonomy-driven bug injection to LLM-based detection and repair, and finally to simulation-based validation, for framework-agnostic OpenQASM 3.0 programs. We further conduct a comprehensive case study using QBugLM to benchmark two LLMs, Claude 4.6 Sonnet and Qwen3 Coder Next, across different prompting strategies, bug categories, and quantum programs. Our results show that iterative feedback is critical, as a single retry raises Pass@1 from below 25% to above 80%. Moreover, simpler structured prompting can even outperform Chain-of-Thought and ReAct for reasoning-capable models under fixed-resource constraints. Our work takes initial steps toward benchmarking LLM capabilities for debugging quantum programs and offers practical insights to support future efforts in automated quantum software repair.

The deployment of embodied artificial intelligence via world-model-based robotics presents a transformative opportunity for blockchain infrastructure, establishing urgent demand for trustworthy data provenance, cross-organizational governance, and incentive-compatible sharing across decentralized ecosystems. Simultaneously, quantum computing advances recognized by the 2025 Nobel Prize in Physics and the Turing Award threaten the cryptographic primitives securing these data economies, creating an interdependent imperative: long-lived verification for embodied AI depends on crypto-agile architectures capable of withstanding quantum adversaries. This tutorial examines blockchain as the coordination layer bridging this dual transition, from financial substrate to foundational Cyber-Physical-Social Systems infrastructure that simultaneously secures against quantum cryptanalysis and enables scalable, trustworthy data economies. The session opens with an immersive AWS Braket demonstration engaging participants with superconducting, trapped-ion, and neutral-atom hardware to assess cryptographic threat timelines and witness ECDSA-to-post-quantum signature transitions. Five integrated modules progress from embodied AI and world-model requirements through quantum hardware reality and evidence-based security migration, to scalable cross-shard architectures via BrokerChain protocols, trustworthy data economies implementing Croissant metadata standards and robotic learning provenance, and industry ecosystem integration for multi-modal cloud deployment. By bridging quantum hardware realities with embodied AI data requirements, this tutorial charts blockchain as unified infrastructure for next-generation decentralized intelligent environments, providing open-source frameworks and roadmaps for architecting quantum-resistant, interoperable, and data-trustworthy systems.

We introduce a universal dilation framework to simulate arbitrary non-Hermitian dynamics x ˙ = L ( t ) x on unitary quantum processors. By imposing algebraic moment-matching conditions on an ancilla, our framework generates diverse families of dilation schemes that unify existing methods and broaden the design space for hardware-aware implementations. A tight-binding dilation that maps the ancilla to a 1D lattice with nearest-neighbor hopping is derived, overcoming the connectivity bottlenecks of dilation schemes. This construction handles general dynamics, including gain, without rescaling and achieves near-optimal complexity, as demonstrated by benchmarks on dissipative wave propagations.

We develop protocols for generating loss-tolerant quantum tree-codes; these are designed to safeguard information against qubit losses, with wide applications in quantum communications. Contrary to previous proposals, our method enables fast encoding and decoding, thereby reducing losses due to the lagging and photon-reordering at the repeater stations. At the hardware level, we show how to achieve this with a single quantum emitter equipped with a feedback mechanism, which we leverage to engineer entangling gates between a fed-back qubit and multiple emitted qubits in parallel. In addition, analyzing typical patterns within the error-correction decoding graphs, we find optimizations of the structure of tree-codes, which enable improved performance by also reducing the code size; these are based on the introduction of in the code, which mimic the intrinsic adaptiveness of the recovery procedure. We show numerically that these improvements together significantly enhance the loss-correction performance. Specifically, focusing on quantum repeater protocols, we show that our fast recovery scheme (decoding-encoding) allows for improved repeater rates with smaller photon numbers per code.

We introduce Single-Shot Cross-Spectroscopy (SSCS), a method for extracting the auto- and cross-power spectral densities of dephasing noise in a qubit pair. The method uses straightforward input, namely, single-shot readouts from single-qubit Ramsey-type experiments, without requiring the reconstruction of qubit energy fluctuations from repeated measurements, and is resilient against errors in state preparation and measurement. We apply it to experimental data from a semiconductor spin-qubit device and obtain noise spectra over five orders of magnitude in frequency (5 mHz–500 Hz). Compared to other techniques, for spin qubits, SSCS enables access to noise correlations in the previously inaccessible intermediate-frequency range (1–500 Hz), and can be further extended with faster readout. The method is directly applicable to other qubit platforms, and the upper frequency it can probe is set by the repetition rate of a single-qubit preparation and measurement.

Abstract We propose the optical simulation of the Lieb–Liniger interaction using one-dimensional (1D) stationary light polaritons (SLPs) with nonlinear self-interaction. Our analysis reveals that the dark-state polariton (DSP) mode of the self-interacting SLP satisfies a Schrödinger-like equation exhibiting the Lieb–Liniger interaction, where both the effective mass and interaction strength can be tuned optically. We demonstrate the transition of the Lieb–Liniger interaction from a repulsion-dominant regime to a thermalization-dominant regime using experimentally achievable parameters. This results in the second-order correlation of the DSP mode spanning from anti-bunching to bunching statistics. By advancing the quantum simulation of the Lieb–Liniger model, our work opens new avenues for exploring complex Lieb–Liniger physics, such as interaction quenching and multi-particle bound states. Moreover, it lays the groundwork for developing novel single-photon sources operating in the anti-bunching regime, featuring narrow bandwidth, directional emission, and built-in quantum memory functionality.

Wide-band gap oxides such as Zn O are favorable hosts for spin defect qubits due to their dilute nuclear spin background and potential for ultrahigh purity. Yet, a deep-level defect qubit with robust optical and spin properties has not been identified in this material. Here, using first-principles calculations, we predict that the molybdenum-vacancy complex, ( Mo Zn v O ) 2 + , exhibits the essential characteristics of an optically addressable spin qubit: a spin-triplet ground state, visible-range optical transitions with high quantum yield, and an unusually small Huang-Rhys factor ( ∼ 5 , compared to 10–30 in known Zn O defects). We further find long spin coherence times ( T 2 ∼ 4 ms ) when both nuclear and impurity spin baths are considered, with paramagnetic impurities setting a threshold concentration of 0.035 ppm. Importantly, the combination of strong spin-orbit coupling and the absence of Jahn-Teller distortion supports spin-selective intersystem crossing and high-fidelity single-shot readout at elevated temperatures and across wide magnetic field ranges. By identifying ZnO as a host for deep-level defect qubits, our work points toward a pathway to scalable, integrable oxide-based quantum technologies and broadens the material foundation for solid-state quantum information science.

Photon blockade—the suppression of multiphoton transmission by quantum nonlinearities—enables on-demand nonclassical light, but it typically requires strong single-emitter coupling and does not improve by simply adding more emitters. We show that this limitation can be overcome when an ensemble of N identical two-level emitters couples to a single cavity mode through a two-photon exchange interaction. Using input-output theory together with a hierarchy of open-system descriptions (exact numerics, a Holstein-Primakoff model, and an approximated analytical treatment), we characterize the steady-state transmission and photon statistics of the two-photon Tavis-Cummings model. We find that blockade is collectively enhanced: the optimal antibunching improves with atom number ( 1 / N 2 scaling of the second-order correlation function) while maintaining near-unit transmission, eliminating the usual brightness-purity trade-off of interference-based weak-coupling schemes. We further identify driving configurations that yield collectively enhanced two-photon blockade, with strong suppression of higher-order autocorrelation functions that deepens with increasing N . The nonclassicality is ultimately limited by decoherence, with emitter dephasing providing the dominant constraint. These results establish collective two-photon light-matter coupling as a scalable route to photon blockade in platforms where individual strong coupling is not achievable.

Abstract We investigate the open-system dynamics of a micromaser quantum battery in the ultrastrong-coupling (USC) regime. The battery consists of a quantized harmonic mode sequentially interacting, via the Rabi Hamiltonian, with a stream of qubits acting as chargers. USC enhances the charging speed but also induces unbounded energy growth and highly mixed cavity states. Dissipation suppresses this behavior, driving the system to a steady state with finite energy and ergotropy. Using optimal control theory, we show that the interplay between USC and dissipation enhances both charging performance and long-term stability against losses.

Abstract The physics of a closed quantum mechanical system is governed by its Hamiltonian. However, in most practical situations, this Hamiltonian is not precisely known, and ultimately all there is are data obtained from measurements on the system. In this work, we introduce a highly scalable, data-driven approach to learning families of interacting many-body Hamiltonians from dynamical data, by bringing together techniques from gradient-based optimization from machine learning with efficient quantum state representations in terms of tensor networks. Our approach is highly practical, experimentally friendly, and intrinsically scalable to allow for system sizes of above 100 spins. In particular, we demonstrate on synthetic data that the algorithm works even if one is restricted to one simple initial state, a small number of single-qubit observables, and time evolution up to relatively short times. For the concrete example of the one-dimensional Heisenberg model our algorithm exhibits an error constant in the system size and scaling as the inverse square root of the size of the data set.

The encoding of classical data into quantum states constitutes the primary performance bottleneck in Quantum Machine Learning (qml) on Noisy Intermediate-Scale Quantum (nisq) devices. No existing framework jointly characterises resource cost, expressivity, and noise robustness, nor provides actionable selection guidelines for practitioners. This survey addresses that gap through a systematic review of 66 primary works (2017-2026) assembled via a PRISMA-adapted protocol across five academic databases. Four principal contributions are made. First, a three-axis cost-expressivity-robustness taxonomy classifies all major encoding families - basis, angle, dense-angle, amplitude, data re-uploading, and IQP - along independently measurable axes. Second, closed-form depth-fidelity bounds under nisq decoherence channels identify the critical gate-error rate p* ~ 10^-3 below which amplitude encoding is viable. Third, a unified treatment of Fourier expressivity, barren-plateau onset, and quantum kernel concentration as functions of the encoding circuit provides the first joint trainability analysis. Fourth, a five-regime decision framework maps (D, n, p, tau) - feature dimension, qubit budget, error rate, and task type - to a hardware-grounded encoding recommendation. The central finding is that for p >= 10^-3, shallow angle-based encodings consistently outperform amplitude encoding in practice, despite the latter's exponential qubit advantage.

The variational quantum eigensolver (VQE) is a promising algorithm for near-term quantum chemistry applications, but selecting optimal ansatz circuits remains challenging. Expressibility, a metric quantifying a circuit's ability to explore the Hilbert space, has been proposed as a guide for ansatz selection, but recent work showed it inconsistently predicts VQE performance under realistic noise for $H_2$. We extend this investigation to cover both $H_2$ and $H_3^+$ under four execution scenarios: ideal, noisy, and noisy with zero-noise extrapolation (ZNE) or probabilistic error cancellation (PEC). We find that error mitigation does not reliably restore expressibility's predictive power. ZNE reduces error for only 4 of 12 $H_2$ circuits and 4 of 6 $H_3^+$ circuits, while PEC actually increases error in 11 of 12 $H_2$ circuits and all 6 $H_3^+$ circuits. We reproduce and extend Saib et al.'s key finding that circuit rankings scramble under noise (Spearman $ρ\approx -0.1$ between ideal and noisy rankings), and identify a new result: ZNE largely preserves noisy rankings ($ρ= +0.80$ for $H_2$) while PEC actively reorders them ($ρ= -0.22$). Noisy expressibility, computed from density matrix simulations, strongly predicts unmitigated performance for $H_3^+$ (Pearson $r = +0.91$, $p = 0.01$), but this metric is computationally intractable at scale. We demonstrate that zero-cost circuit topology metrics such as two-qubit gate count provide comparable or superior predictive power for PEC degradation ($r = +0.96$ for $H_3^+$), while standard expressibility best predicts noisy and ZNE performance for $H_2$ ($r = +0.74$ and $r = +0.77$).

We construct a local decoder for the 2D toric code using ideas from the hierarchical classical cellular automata of Tsirelson and Gács. Our decoder is a circuit of strictly local quantum operations preserving a logical state for exponential time in the presence of circuit-level noise without the need for non-local classical computation or communication. Our construction is not translation invariant in spacetime, but can be made time-translation invariant in 3D with stacks of 2D toric codes. This solves the open problem of constructing a local topological quantum memory below four dimensions.

Variational counterdiabatic (CD) driving is a disciplined and widely used method to robustly control quantum many-body systems by mimicking adiabatic processes with high fidelity and reduced duration. Central to this technique is a universal structure of the adiabatic gauge potential (AGP) over a parameterized Hamiltonian. Here, we reveal that introducing a new degree of freedom into the theory of the AGP can significantly improve variational CD driving. Specifically, we find that the algebraic characterization of the AGP is not unique, and we exploit this nonuniqueness to develop the for deriving a refined driving protocol. This approach extends the conventional method in two aspects: it assigns customized weights to matrix elements relevant to specific problems, and it effectively incorporates nonlocal information into local driving coefficients. We also develop an efficient numerical algorithm to compute the refined driving protocol using computer algebra. Our framework is broadly applicable and, in principle, it can replace any previous use of variational CD driving. We demonstrate its practicality by applying it to adiabatic evolution along the ground state of a parameterized Hamiltonian. This proposal outperforms the conventional method in terms of fidelity, as confirmed by extensive numerical simulations on quantum Ising models.

Sixth-generation (6G) wireless networks will underpin ultra-dense Industrial IoT (IIoT) ecosystems in which resource-constrained Far-Edge devices -- autonomous mobile robots, industrial actuators, connected vehicles -- must simultaneously satisfy sub-millisecond latency, $10^{-7}$-class reliability, and decades-long cryptographic security. Current architectures delegate Digital Twin (DT) computation to centralised cloud or Mobile Edge Computing (MEC) servers, incurring prohibitive round-trip latency, and rely on classical public-key cryptography vulnerable to quantum attacks under the harvest-now, decrypt-later (HNDL) threat model. We propose Q-FE, a Quantum-Native 6G Far-Edge architecture integrating three co-designed components: (i) Micro-Digital Twins ($μ$DTs) co-located with 6G base stations and high-capability endpoints; (ii) a Cross-Layer Post-Quantum Key Exchange module embedding CSIDH-512 isogeny key material directly within MAC-layer control frames, exploiting the scheme's uniquely compact keys ($\le 64$ bytes) to avoid packet fragmentation; and (iii) an Asynchronous Federated Learning (AFL) protocol governed by lightweight DAG smart contracts at MEC nodes, eliminating straggler bottlenecks and preventing model-poisoning and Sybil attacks without exposing raw data. End-to-end simulations (NS-3 + PySyft) demonstrate that Q-FE reduces MAC-layer overhead by 62% versus ML-KEM/Kyber-1024, maintains P99.9 URLLC latency at 0.78 ms, and accelerates global-model convergence by 31% over synchronous Federated Learning. Protocol complexity analysis confirms $O(N \log R)$ per aggregation round, and $μ$DT handover migration completes in $1.9 \pm 0.3$ ms across $10^4$ simulated events. A formal threat model confirms resilience against quantum eavesdropping, model-poisoning, and Sybil attacks.

This post was contributed to by Zia Mohammad, Scott Smart, Yuvraj Mohan, Mike Piech, and Rebecca Malamud Figure 1: A Rigetti quantum processing unit (QPU) inside a dilution refrigerator. Photo by Drew Bird. Amazon Braket enables customers to design and run quantum algorithms on a broad selection of quantum hardware through a unified interface. On April 7, 2026, we expanded the hardware available on Braket with the general availability of Rigetti Computing’s Cepheus-1-108Q , a 108-qubit superconducting quantum processing unit (QPU). Cepheus-1-108Q is the first gate-based quantum device with more than 100 qubits available on Amazon Braket. It replaces the Ankaa-3 system and represents the third generation of Rigetti hardware on the service. The device is built using Rigetti’s proprietary multi-chip architecture that tiles twelve 9-qubit chiplets into a single processor. It is physically located in the United States and available through the US West (N. California) Region. Device overview Cepheus-1-108Q joins Amazon Braket’s quantum hardware portfolio, giving customers access to a 108-qubit superconducting system for workflows in quantum computing applications. Customers worldwide can run experiments using on-demand access for quantum tasks, priority access through Amazon Braket Hybrid Jobs for variational quantum algorithms, or dedicated reservations through Braket Direct on a per-hour basis. The device provides 20 hours of quantum task processing availability every day of the week. Figure 2: The Cepheus-1-108Q device page in the Amazon Braket Management Console. Technical architecture Cepheus-1-108Q uses Rigetti’s modular multi-chip architecture. The processor consists of a 3×4 array of twelve superconducting 9-qubit chiplets tiled together, with qubits connected via tunable couplers and intermodule couplers (IMCs). This approach builds on Rigetti’s Cepheus-1-36Q system, tripling the number of chiplets and total qubit count. Figure 3: The Cepheus-1-108Q multi-chip pr

We present a new simulation-secure quantum oblivious transfer (QOT) protocol based on one-way functions in the plain model. With a focus on practical implementation, our protocol surpasses prior works in efficiency, promising feasible experimental realization. We address potential experimental errors and their correction, offering analytical expressions to facilitate the analysis of the required quantum resources. Technically, we achieve simulation security for QOT through an e q u i v o c a l and r e l a x e d &amp;#x2212; e x t r a c t a b l e quantum bit commitment.

We investigate quantum cellular automata (QCA) on one-dimensional spin systems defined over a subalgebra of the full local operator algebra – the symmetric subalgebra under a finite Abelian group symmetry G . For systems where each site carries a regular representation of G , we establish a complete classification of such subalgebra QCAs based on two topological invariants: (1) a surjective homomorphism from the group of subalgebra QCAs to the group of anyon permutation symmetries in a ( 2 + 1 ) d G gauge theory; and (2) a generalization of the Gross-Nesme-Vogts-Werner (GNVW) index that characterizes the flow of the symmetric subalgebra. Specifically, two subalgebra QCAs correspond to the same anyon permutation and share the same index if and only if they differ by a finite-depth unitary circuit composed of G -symmetric local gates. We also identify a set of operations that generate all subalgebra QCAs through finite compositions. As an example, we examine the Kramers-Wannier duality on a Z 2 symmetric subalgebra, demonstrating that it maps to the e - m permutation in the two-dimensional toric code and has an irrational index of 2 . Therefore, it cannot be extended to a QCA over the full local operator algebra and mixes nontrivially with lattice translations.

This paper explores the sensitivity gains afforded by spin-squeezed states in atom interferometry, in particular using Bragg diffraction. We introduce a generalised input-output formalism that accurately describes realistic, non-unitary interferometers, including losses due to velocity selectivity and scattering into undesired momentum states. This formalism is applied to evaluate the performance of one-axis twisted spin-squeezed states in improving phase sensitivity. Our results show that by carefully optimising the parameters of the Bragg beam splitters and controlling the degree of squeezing, it is possible to improve the sensitivity of the interferometer by several dB with respect to the standard quantum limit despite realistic levels of losses in light pulse operations. However, the analysis also highlights the challenges associated with achieving these improvements in practice, most notably the impact of finite temperature on the benefits of entanglement. The results suggest ways of optimising interferometric setups to exploit quantum entanglement under realistic conditions, thereby contributing to advances in precision metrology with atom interferometers.

Nondegenerate Josephson mixers (JMs), formed by coupling two different transmission-line resonators to Josephson ring modulators (JRMs), are vital and versatile devices capable of processing microwave signals at the quantum limit. Owing to the lossless nondegenerate three-wave mixing process enabled by the JRM, JMs can perform phase-preserving amplification of quantum signals, generate two-mode squeezed states, and perform noiseless frequency conversion. However, due to their limited bandwidth and saturation power, such resonator-based JMs are generally unable to simultaneously process frequency-multiplexed signals required in large quantum processors. To overcome this longstanding dual challenge, we redesign the JRM parameters by optimizing its inductances to suppress higher order mixing products and engineer its electromagnetic environment by incorporating lumped-element coupled-mode networks between the JRM and the two distinct ports of the JM. By implementing these strategies, we measure for JMs realized with four coupled modes per port, operated in amplification (conversion), bandwidths of about 400 MHz (700 MHz) with power reflections above 10 dB (below − 10 dB) and saturation powers of about − 110 dBm at 15 dB ( − 91 dBm at − 26 dB). Similarly, we demonstrate for a low external quality factor resonant-mode JM operated in conversion, a maximum bandwidth of about 670 MHz with power reflections below − 10 dB and a maximum saturation power of about − 86 dBm at − 17 dB. Such nondegenerate JMs with enhanced bandwidths and saturation powers could serve in a variety of frequency-multiplexed settings ranging from high-fidelity qubit readout and unidirectional routing of quantum signals to the generation of remote entanglement with continuous variables.

Quantum compilers that reduce the number of T gates are essential for minimizing the overhead of fault-tolerant quantum computation. Achieving further T -count reduction calls for identifying equivalent circuit transformation rules beyond those utilized in existing tools. In this paper, we rewrite any given Clifford + T circuit using a Clifford block followed by a sequential Pauli-based computation and introduce a nontrivial, ancilla-free transformation rule, the multiproduct commutation relation (MCR). MCR constructs gate sequences based on specific commutation properties among multi-Pauli operators, yielding seemingly noncommutative instances that can be commuted, thereby enabling gate orderings that cannot be derived from pairwise commutation alone. We also propose the MCR Compiler, which incorporates MCR-based transformations as an optimization pass. To evaluate its effect, we use a benchmark circuit dataset generated through quantum circuit unoptimization. This approach intentionally adds redundancy to the circuit while keeping its equivalence, allowing a quantitative evaluation of compiler performance by comparison with the original circuit. Our numerical experiments reveal that the MCR Compiler achieves further T -count reduction beyond current compilers, establishing MCR-based transformations as a practical optimization primitive. These results highlight an untapped opportunity to enhance the optimization capabilities of quantum compilers.

Abstract All-solid-state cavity quantum electrodynamics (cQED) has drawn significant research interest because of its potential applications in the development of large-scale integrated quantum photonics. However, the long-lasting issues associated with local spectral tuning of the cavity and emitter, in-plane light confinement for efficient light routing, have hindered its on-chip scalable implementations. Here, we overcome these limitations by proposing and demonstrating a hybrid chip-integrated solid-state cQED device with strong in-plane optical mode confinement. The device consists of semiconducting quantum dots (QDs) integrated onto a thin-film lithium niobate (TFLN) microring resonator. By exploring the TFLN’s piezoelectric strain and electro-optic (EO) properties, we have realized local spectral tuning for waveguide-coupled QDs up to 4.82 nm (7.30 meV), enabling on-chip deterministic single-photon emission with a Purcell factor of 3.52. When further combining the independent EO effect-based cavity tuning, we demonstrate an on-chip wavelength-tunable cQED device with Purcell factors over 1.89 in a 0.30 nm (0.45 meV) tuning range, 230 times more than the reported transform-limited linewidth of the QDs emission. The successful demonstration of scalable cQED with circuits-compatible local strain and EO tuning methods opens the avenue to scale up all-solid-state cQED devices in large-scale quantum photonic circuits.

Deep neural networks (DNNs) have achieved state-of-the-art performance across diverse domains. However, typical Von Neumann compute paradigms face severe memory bottlenecks. Emerging near-memory and compute-in-memory approaches alleviate this but incur significant peripheral overhead. Computational Random Access Memory (CRAM) based on MRAM enables in-situ logic without peripheral overhead, offering a dense, energy-efficient solution. However, probabilistic MRAM switching induces gate-level errors that limit the scalability and reliability of CRAM for accelerating DNN. Moreover, the large number of sequential MRAM writes severely constrains CRAM throughput. To address these challenges, we propose an error-resilient CRAM (CRAM-ER) architecture for scalable in-memory matrix-vector multiplications (MVMs). Our error-aware hardware-software co-design framework leverages a hybrid spintronic-CRAM + CMOS adder-tree architecture to mitigate the impact of device-level errors, demonstrating MVM functionality with high area and energy efficiency. We further develop an error-aware model fine-tuning and fine-grained error correction for enhanced error resilience. Evaluations of the CMOS+spintronic hybrid architecture on DNN benchmarks show near-lossless accuracy while reducing CRAM latency by up to 2 orders of magnitude, outperforming CPU/GPU+high-bandwidth DRAM in both energy efficiency and energy-delay product.

Compile-time optimization is important for improving the efficiency and reliability of quantum circuits on current noisy hardware. While many existing methods simplify circuits using structural patterns or quantum-state information, most of them target only unitary circuits and do not support dynamic circuits with mid-circuit measurements and classical feedforward. In this work, we present Branch-Aware Quantum Constant Propagation (BQCP), a compile-time analysis for dynamic circuits. BQCP extends Quantum Constant Propagation (QCP) by tracking the classical information produced by mid-circuit measurements together with the corresponding post-measurement quantum states across different execution branches. This enables path-sensitive reasoning inside conditional blocks and more precise information propagation than QCP. To keep the analysis scalable, we bound both the size of the quantum-state representation and the number of tracked branches. Using the information inferred by the analysis, we apply semantics-preserving simplifications to circuit operations. We prove the soundness of both the analysis and the simplifications. Experimental results on both application-driven and synthetic benchmarks show that, on dynamic circuits, our method consistently achieves larger reductions than other existing passes including QCP.