Papers

Photonic integrated circuits offer a scalable and robust route toward quantum information technologies by consolidating photon sources and linear optical networks onto compact, wafer-manufacturable chips. Although silicon photonics has enabled diverse discrete-variable quantum breakthroughs – spanning multiphoton entanglement, quantum networking, and photonic qubit fusion for quantum computing – scaling these platforms beyond proof-of-principle demonstrations remains severely constrained by a critical system-level bottleneck. Optical loss compounds rapidly across photon generation, routing, and state analysis, causing multiphoton generation probabilities to plummet exponentially as circuit depth and complexity grow. Here we overcome this rate-loss barrier by demonstrating a monolithic, ultralow-loss silicon nitride (Si$_3$N$_4$) integrated photonic platform engineered for high-performance discrete-variable quantum information processing. Our architecture seamlessly integrates narrowband photon-pair sources with low-loss qubit-fusion circuits and reconfigurable state-analysis interferometers. The on-chip sources prepare Einstein-Podolsky-Rosen (EPR) states with a fidelity of 0.9875(3) and exhibit near-unity photon indistinguishability, yielding a heralded Hong-Ou-Mandel interference visibility of 0.990(6). By executing on-chip fusion of two EPR states, we synthesize and characterize four-photon Greenberger-Horne-Zeilinger states with a record fidelity of 0.943(8) and a fourfold count rate of 27 Hz – more than two orders of magnitude higher than previous silicon-photonic implementations. Combined with standard CMOS-compatible fabrication on 150-mm-diameter wafers, these results establish ultralow-loss Si$_3$N$_4$ integrated photonics as a definitive, manufacturable platform for deployable, large-scale quantum information processors.

Quantum chemistry is one of the major potential applications in quantum computation. Currently there is a considerable focus on relatively small active spaces as a consequence of hardware noise and exponential bottlenecks in simulations. In the long run, there will be an increasing demand in reliable approximations for larger systems – both, as initial states for projective algorithms like the quantum phase estimation or for the evaluation of dynamical properties. While numerous approaches to select active spaces and extrapolate basis set accuracy exist, there is currently no consistent approach that results in a single quantum circuit for the total system. In this work, we combine hybrid Fermionic-Bosonic encodings with the structured approach of Quantum Valence Bond Theory to directly construct quantum circuits for comparably large molecular systems. With this approach we are able to push simulability barrier of variational quantum eigensolvers towards chemically relevant systems and demonstrate circuit designs that outperform active space counterparts and achieve good approximations with respect to the exact solutions.

Graphs provide a natural language for relational data in chemistry, biology and optimisation. Graph neural networks (GNNs) have driven much of the recent progress in learning from such data through message passing, a single primitive that generalises convolution and attention. Quantum counterparts have been proposed, but with limited connection to message passing and few guarantees on performance or scalability. More broadly, the trainability of variational quantum circuits is a recognised bottleneck for their wide applicability, and pre-training has emerged as one way to address it. Yet for a quantum model to be useful, it must offer expressivity guarantees along with demonstrable scalability. Here we show how a quantum graph neural network can be built to perform message passing, to be permutation equivariant, and to sit at a chosen level of the Weisfeiler-Leman hierarchy, the standard measure of how finely a model can tell graphs apart. We show that, as for classical GNNs, the training can be done first on small graph instances, allowing for a pre-training that can mitigate usual training issues, and its output can be read out at a cost that stays low as the graph grows. We validate the framework in large-scale simulations of up to 56 qubits across three datasets, on synthetic graphs that ordinary message passing cannot separate, on molecular property prediction, and on the travelling salesperson problem. Our framework opens a path for near-term quantum algorithms with theoretical guarantees and practical scalability, bringing the principles of graph learning into quantum circuit design.

We revisit the quantum annealing problem in the non-Hermitian transverse-field Ising model. We determine, both analytically and numerically, the intrinsic transition probabilities and the resulting defect density. Our results reveal that, unlike the Hermitian case where defect production is dominated by modes near the gap-closing point, the non-Hermitian dynamics involve significant contributions from broad momentum sectors. We find that, depending on the dissipation strength, the defect density exhibits standard Kibble-Zurek scaling, anti-Kibble-Zurek behavior, and a suppression faster than the Kibble-Zurek prediction. We demonstrate that these deviations from the standard Kibble-Zurek scaling can be understood in terms of the underlying excitation probabilities. Specifically, the fast decay of the defect density originates from a vanishing excitation probability spanning a range of annealing times across all allowed modes, even at the gap-closing points. In contrast, the anti-Kibble-Zurek behavior arises from supplementary excitations facilitated by dissipation over a broad range of allowed modes, particularly those situated away from the gap-closing region.

We use a primordial Majorana field as a fermionic probe of quantum correlations during inflation. Working in a torsion-free FLRW spacetime, we derive the two-component Majorana mode equations in an axion-inflation background and construct the corresponding quadratic Hamiltonian in the paired momentum basis. Hamiltonian diagonalization and the fermionic squeezing formalism are shown to give the same Bogoliubov transformation, providing a direct map from the Majorana mode functions to the instantaneous occupation number and to the two-mode state of each $(\boldsymbol{k},-\boldsymbol{k})$ pair. Because Fermi statistics restricts each helicity sector to the vacuum and one-pair states, the resulting Hilbert space is finite and the bipartite quantum-information measures can be evaluated explicitly. We compute the von Neumann entropy of the reduced mode and the logarithmic negativity of the Majorana pair. Both diagnostics indicate that sufficiently light Majorana modes can retain enhanced super-horizon bipartite quantumness, with the logarithmic negativity making the residual inseparability especially explicit. Our result does not by itself constitute an observational Bell test or a complete decoherence analysis; rather, it identifies a Pauli-bounded matter sector in which horizon exit alone is not sufficient to erase the quantum signature encoded in the two-mode state, thereby motivating an open-system study of how reheating and inflaton-induced interactions classicalize primordial fermionic probes.

Quantum neural networks have emerged as powerful models for approximating nonlinear functions. Yet their use in solving integro-differential equations (IDEs) and fractional integro-partial differential equations (FIPDEs), which involve inherently nonlocal operators, remains unexplored. This work introduces a quantum physics-informed neural network (QPINN) framework that combines a quantum neural network with the governing equations of general nonlinear IDEs and FIPDEs. The proposed quantum network uses an affine feature map and variational quantum circuits to produce trial solutions with explicit trigonometric structure. We prove a quantitative $L^{2}(\mu)$ universal approximation theorem for this architecture, achieving a convergence rate of $\mathcal{O}(n^{-1/2})$. This extends classical Fourier approximation theory to quantum circuits for physics-informed learning. We propose two QPINN variants: the numerical-quadrature QPINN (N-QPINN), which handles nonlocal integrals and fractional operators via high-order numerical quadrature while computing local derivatives through automatic differentiation of quantum trial solutions; and the auxiliary-function QPINN (A-QPINN), which eliminates numerical quadrature by introducing auxiliary variables that reformulate each integro-differential equation as an equivalent coupled system of partial differential equations, enabling a multi-output quantum neural network to simultaneously represent the solution and its associated variables. A series of numerical experiments demonstrates that the proposed QPINN framework accurately captures the behavior of nonlinear IDEs and FIPDEs and outperforms classical physics-informed neural networks.

Holonomic quantum computation offers a promising route to robust quantum gates, but decoherence remains a central obstacle in realistic implementations. Here we develop a nonadiabatic holonomic scheme for a driven three-level system in the no-jump regime described by an effective non-Hermitian Hamiltonian. Within a biorthogonal framework, tailored complex pulses enforce exact closure of the computational-subspace evolution at the final time despite the underlying nonunitary dynamics, enabling arbitrary single-qubit holonomic gates without requiring cyclic evolution in its orthogonal complement. In contrast to existing non-Hermitian treatments, which either neglect the overall exponential prefactor or, in adiabatic settings, include dissipation only on the auxiliary excited level, our scheme incorporates decay and dephasing of all bare eigenstates directly into the pulse design, so that dissipation does not reduce the no-jump gate fidelity.

We counterintuitively present a Hermitian squeezing-Dicke model as a minimal setting for non-Hermitian physics in many-body light-matter systems. It enables the realization of a non-Hermitian Hamiltonian of interest using a Hermitian quadratic bosonic system. Unlike previous dissipation-driven non-Hermitian mechanisms, effective parity-time ($\mathcal{PT}$) symmetry arises purely from squeezing and exchanges gainy and lossy eigenmodes. We identify non-Hermiticity of an anomalous superradiant phase for strong spins squeezing, exhibiting spontaneous breaking of the unique $\mathcal{PT}$ symmetry beyond $Z_2$ symmetries. Such exotic phase exhibits a complex excitation spectrum and undergoes a dynamical phase transition to a conventional superradiant phase at an exceptional point. An artificial magnetic field combined with the broken Hermiticity yields nonreciprocal dynamics with striking quantum amplification, exhibiting unidirectional enhanced transmission. Our Hermitian light-matter system offers an alternative pathway to exotic non-Hermitian physics and nonreciprocal quantum amplification.

Accurately solving the electronic Schrödinger equation for strongly correlated systems remains a central challenge in quantum chemistry, where the exponential growth of configuration space limits the applicability of exact methods. Selected Configuration Interaction (SCI) algorithms address this challenge by adaptively constructing compact determinantal expansions, yet their efficiency depends critically on the quality of the sampling strategy used to identify chemically important configurations. Here we introduce the Handover Iterative Neural Quantum State (HI-NQS) algorithm, which embeds a classically trained autoregressive Transformer neural quantum state within the iterative sample–diagonalize–update framework of Sample-Based Quantum Diagonalization. A dual-channel Transformer architecture with explicit spin-up/spin-down cross-attention encodes fermionic spin structure as an architectural inductive bias, enabling expressive and physically informed wavefunction representations. After each subspace diagonalization, the resulting eigenvector is distilled back into the network through a factorized spin-marginal teacher signal, establishing a closed feedback loop between generative sampling and exact diagonalization. Benchmarks across a range of small molecules and a systematic nitrogen active-space series demonstrate that HI-NQS achieves chemical accuracy on all systems tested, with determinant-count scaling substantially more favorable than conventional CIPSI-based SCI for all but the smallest active spaces. All calculations are performed on GPU hardware without quantum computing resources, establishing HI-NQS as an efficient and scalable purely classical approach to the selected configuration interaction problem.

Nonlinear 2D materials such as 3R-phase molybdenum disulfide (3R-MoS2) offer strong second-order optical nonlinearities in an atomically thin platform, making them attractive for on-chip frequency conversion, quantum light generation, and integrated nonlinear nanophotonics. However, the second harmonic generation (SHG) efficiency of monolayer or few-layer 3R-MoS2 deposited on planar substrates remains fundamentally limited by weak light-matter interaction, poor phase matching, and small interaction volumes. Here, we introduce NanoPhotoNet-PINL, a physics informed AI-driven inverse design framework based on a hybrid one-dimensional convolutional neural network and deep neural network autoencoder, tailored for nonlinear MLMs metasurfaces. The model directly maps target dual-resonant reflection spectra at the fundamental and second-harmonic wavelengths to the required multi-layer geometries and material compositions that maximize the effective nonlinear overlap with an embedded 3R-MoS2 sheet. By integrating Maxwell-based nonlinear electrodynamics into the inverse design loop, we compute the second-harmonic conversion efficiency and modal overlap factors for each predicted MLMs design, enabling physics-guided training and evaluation. Our approach achieves an inverse-design prediction efficiency exceeding ~99.2 % along the linear spectral manifold, while the optimized dual-resonant MLMs yield more than three orders of magnitude enhancement in SHG intensity compared to a bare 3R-MoS2 flake on a planar substrate. NanoPhotoNet-PINL establishes a generalizable paradigm for intelligent inverse design of nonlinear multi-layer metasurfaces and phase-matched dual-resonant cavities for high-efficiency second-order processes.

We propose an array of Ramsey-type interferometers using $N$ superposition states, $(\vert 0 \rangle + \vert 1\rangle)^{\otimes N}$, as a sensor to detect wave-like dark matter. After exposure to the dark matter wave, which induces coherent qubit transitions, the signal is the imbalance between the numbers of 0 and 1 outcomes. The signal-to-noise ratio in this scheme is proportional to $N \alpha^2$, where $\alpha$ is the coupling of dark matter to the qubits, and thus the sensitivity to the coupling scales as $\delta \alpha \sim 1 / \sqrt{N}$. For comparison, in the detection scheme based on the Rabi-type transition, $\vert 0 \rangle \to \vert 1\rangle$, this scaling is achieved only when $N$ highly entangled qubits are used. Since the Ramsey-type measurement does not require entangled states, one can consider much larger $N$ by simply placing a large number of qubits within the de Broglie wavelength of the dark matter. We demonstrate that, using trapped-ion qubits in linear Paul traps as the sensor, the projected sensitivity to the coupling matches or surpasses existing laboratory, astrophysical, and cosmological bounds for $N \gtrsim 10^6$-$10^8$. We also evaluate its sensitivity to high-frequency gravitational waves. Our general framework should, in principle, be useful for other quantum sensing platforms.

Quantum fast-forwarding (QFF) is usually formulated for reversible Markov chains, where the projected quantum walk evolution is exactly governed by Chebyshev polynomials of a Hermitian discriminant matrix. We study whether this framework can be extended to nonreversible dynamics for an $\alpha$-perturbed $n$-cycle Markov chain, which preserves circulant structure while introducing controlled irreversibility. We show that the nonreversible case has a fundamental obstruction: for $\alpha \neq 0$, the eigenvalues of $P_\alpha$ leave the interval $[-1,1]$, so $T_m(P_\alpha)$ is not uniformly bounded and cannot arise as an exact unitary compression for all times. Thus, exact Chebyshev-based QFF does not extend directly beyond reversibility. Nevertheless, we obtain a finite-time approximation result using truncated Chebyshev and LCU techniques. The evolution $P_\alpha^t$ can be approximated with degree $\tau=O\left(|\alpha|t+\sqrt{t\log(t/\eta)}\right),$ which recovers the reversible $O(\sqrt t)$ behavior only in the perturbative regime $|\alpha|=O(t^{-1/2})$. This identifies a nearly reversible regime where QFF survives perturbatively and quantifies how irreversibility degrades the speedup.

We consider the problem of distinguishing sets of quantum product states with local operations and classical communication (LOCC). Recent work has used graph theory to identify sets of product states distinguishable with one-way LOCC. We extend these efforts to full two-way LOCC, with the first significant analysis of the set of graphs corresponding to bipartite product states that can be distinguished with two-way protocols after finitely many steps. We derive basic closure properties of the set of distinguishable graphs and identify some classes of graphs that guarantee local distinguishability and some graphs that do not. We also include several examples and forward-looking comments.

Cavity-assisted photon scattering (CAPS) is a powerful mechanism for realizing strong interactions between the internal states of stationary qubits and flying photons, underpinning a broad range of hybrid atom-photon protocols including remote entanglement generation and heralded atom-photon gates. Recently, the motional quantum state has emerged as an important building block for quantum information processing with atomic qubits, both as a coherently controllable degree of freedom and as a fundamental error channel through undesired spin-motion coupling. For the resonant-coupling regime of cavity quantum electrodynamics relevant to CAPS operations, however, the analytical formulation of spin-motion-photon coupling has so far remained elusive. Here, we develop a complete analytical framework for CAPS that incorporates the coherent interaction between atomic motion and a reflected photon by extending scattering theory to include the motional degree of freedom. The resulting compact operator-based input-output relation applies uniformly across various cavity geometries, spin-dependent trapping potentials, and nonidentical multiple spins. As an exemplary application, we use the framework to elucidate how atomic motion affects CAPS-based atom-photon gates, identifying the parameter regimes that suppress motion-induced errors. Our framework provides a theoretical foundation both for mitigating motional errors in CAPS operations and for deliberately exploiting motion-photon interaction at the atom-photon interface.

Bloch oscillations (BOs) represent a paradigmatic manifestation of force-driven band dynamics in lattices, conventionally characterized by continuous quasimomentum evolution and smooth periodic trajectories. Here we show that non-Hermiticity qualitatively changes this paradigm, introducing nonsmooth BOs characterized by cusp-like real-space trajectories and abrupt momentum jumps. Reversing the force switches the dynamics between smooth and nonsmooth BOs, enabling strongly nonreciprocal dynamics. We derive a universal relation for the critical force that governs the nonsmooth-to-smooth dynamical transition in general one-dimensional lattices, which is induced by a pitchfork bifurcation in momentum space. Our work establishes a unified framework for non-Hermitian BOs and uncovers a fundamental bifurcation mechanism that can generate nonsmooth wave transport in entirely linear systems.

We investigate the algebraic structure underlying the Lindblad equation for finite-dimensional open quantum systems. By introducing a suitable operator representation of the Liouville superoperator, we show that the dynamics can be formulated in terms of a closed algebra of Hermitian operators that is independent of the particular physical model. This formulation reveals that dissipative dynamics requires a substantially richer algebraic structure than purely unitary evolution, thereby providing a clear characterization of the additional complexity introduced by the Lindbladian. The resulting framework naturally leads to parametrizations of the dynamical map and to differential equations governing its evolution. We further derive recursion relations that enable the efficient construction of the algebra for systems of increasing dimension. Because the algebraic basis is universal, while all model-dependent information enters through a single set of coefficients, the proposed approach significantly reduces the computational cost of constructing the Liouville superoperator compared with direct methods. To facilitate the implementation of the method, we provide a Mathematica notebook containing a one-qubit example that can be systematically extended to an arbitrary number of qubits. The proposed framework therefore provides both a general mathematical description of finite-dimensional Lindblad dynamics and a practical foundation for efficient analytical and numerical implementations.

Arguments for emergent spacetime require that quantum typicality, the generic absence of inter-subsystem correlations, persists on the physical Hilbert space of a gauge theory, where non-Abelian constraints could in principle inject geometry-supporting entanglement. Using $SU(2)$ lattice gauge theory on two-dimensional tori ($d_{\mathrm{phys}}$ up to $4{,}193$), we show that it does: the typical mutual information between strictly disjoint links matches an exact parameter-free analytical prediction combining a microcanonical baseline with Haar-random fluctuations. The Kogut-Susskind Hamiltonian generates correlations from states of definite geometry (such as the electric vacuum), while generic states show only regression to the mean, establishing that the arrow of correlation growth requires a non-generic initial condition.

Open quantum systems typically lose their initial memory due to the environmental decoherence resulting in thermalization. We demonstrate a striking breakdown of this paradigm in a head-to-tail Bose-Josephson junction, which is described by an intrinsically momentum-coupled Caldeira-Leggett model. Through exact non-Markov Langevin simulations, we discover a novel type of non-ergodic dynamical phase transitions into a running state, which has no counterpart in Markov limit. Crucially, we reveal that this transition is fundamentally governed by a zero-mode exceptional point emerging from the non-Markov friction. This topological origin is characterized by the winding of the response function. Finally, numerical quantum simulations of an equivalent driven XXZ spin chain confirm that this exceptional-point-induced signature robustly survives as a dynamical crossover against strong quantum fluctuations and the dynamical backreaction of the environment. This macroscopic robustness offers a promising platform for long-lived quantum memories in dissipative environments.

Non-local quantum computation (NLQC) studies how two collaborating players can implement channels on distributed systems using a single simultaneous round of quantum communication and shared entanglement. NLQC has applications in diverse areas, ranging from quantum position-verification to quantum gravity. Recently, it has been realized that the relationships among families of NLQC tasks are highly structured: many seemingly distinct tasks are related by reductions, wherein implementations of one task can be used to efficiently implement a second task. This is analogous to the notion of reduction in complexity theory, and reveals the relative hardness of NLQC tasks. In this work we continue the study of reductions among NLQC tasks. We focus on NLQC examples of the greatest interest in quantum position-verification; in particular examples involving large classical inputs and fixed-size quantum inputs, since these constitute the most feasible protocols for position-verification schemes. Within this setting, we find many new relationships among NLQC tasks. For instance, protocols for the simplest example of redirecting a quantum system based on a classical control imply protocols for controlled single qubit measurements in arbitrary bases, the controlled application of any Clifford unitary, and even the controlled application of any unitary of the form $U=C_1DC_0$ with $D$ an arbitrary diagonal unitary and $C_0, C_1$ Clifford circuits. This implies that many feasible position-verification schemes have the same asymptotic scaling for their entanglement cost, and hence a similar level of security. Our techniques rely on ideas from gate teleportation and measurement based quantum computation, among other areas, bringing several new strategies into NLQC which may be of independent interest.

Device-independent quantum key distribution (DI-QKD) guarantees security with a minimal set of assumptions about the experimental setup. The challenge posed by its implementation could be tackled using routed Bell tests with entanglement swapping, or distant Bell state measurement (BSM) units. However, practical distances still require local tests with close-to-ideal violations or BSMs with high efficiency. We propose a DI-QKD protocol based on a multi-port BSM, and multiple sources and measurement devices, where in each round, routed tests are performed on randomly selected local devices. The violation of local Bell tests is checked even for the subset of rounds where successful BSM projections are achieved. By requiring that this violation remain consistent with the overall average, we specifically show improvements in the critical efficiencies of a three-port BSM, of up to $6\%$ in absolute terms for high visibilities. Without ideal violations, we also achieve arbitrarily small efficiencies with arbitrarily many BSM ports. Our approach enables long-distance DI-QKD, with access to highly efficient loophole-free routing setups, and multiple local tests (possibly imperfect) with very high local detection efficiencies. Remarkably, it avoids the use of quantum memories and the need for long-range Bell tests. Finally, we extend the concept of routing to dimension witnesses, where qubit-bounded sources send states to the BSM. This can be seen as a semi-device-independent extension of the aforementioned protocol.

Autoencoders transformed classical machine learning by solving the curse of dimensionality, enabling principled weight initialization and learning compact, structured representations. In this work, we extend this paradigm to quantum machine learning by introducing a variational autoencoder framework that learns task-specific quantum embeddings of classical data. We demonstrate that high-dimensional datasets, including ImageNet, can be compressed into a 13-qubit quantum representation while remaining reconstructable through a learned decoder. On MNIST (3 vs 5), our approach achieves 98.5% validation accuracy using a circuit-centric quantum classifier, within 1.2 percentage points of a classical neural network baseline (99.7%) and more than 30 percentage points above a naive amplitude-embedding approach. Unlike amplitude embeddings, which require full quantum state tomography for recovery, or angle embeddings, which generally rely on circuit inversion under restrictive assumptions, the proposed framework reconstructs the original data from only a polynomial number of measurements. The framework was further validated on IBM quantum hardware, confirming that the learned embeddings remain stable and reconstructable under real device noise.

Metasurfaces are emerging as a promising platform for photon-pair generation through spontaneous parametric down-conversion, thanks to their compactness, integrability, and intrinsic multifunctionality, which enables the engineering of complex quantum states. However, their full potential remains only partially exploited because the physical mechanisms governing key properties of the generated photon pairs, such as generation efficiency and emission directionality, are not yet fully understood. As a result, metasurface designs and experimental configurations are often optimized through trial-and-error procedures. Here, we theoretically investigate the main mechanisms that control photon-pair generation and detection by studying how different pump configurations and measurement geometries affect the generation efficiency, emission directionality, and collection efficiency of the emitted photon pairs. This framework allows us to interpret existing experimental results and to provide general guidelines for the design of metasurfaces and the choice of experimental configurations in future experiments. Finally, we show that substrate thickness and multilayer configurations represent additional degrees of freedom for quantum metasurface design and can be engineered to enhance the generation efficiency and control the emission directionality, providing a new route for the optimization of photon-pair sources based on metasurfaces.

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 prove that the colored Hofstadter butterfly has a many-body interpretation for a broad class of weakly interacting lattice fermion systems. Starting from a spectral gap of a Hofstadter-like one-particle Hamiltonian at arbitrary magnetic flux $b$, we construct an open region in the three-dimensional parameter space $(b,\mu,\lambda)$ of magnetic field, chemical potential, and interaction strength on which the infinite-volume interacting system has locally unique gapped ground states. The construction combines quasi-adiabatic continuation in the interaction strength with denominator-independent magnetic perturbation estimates, and therefore covers both commensurate and incommensurate fluxes, where no finite magnetic unit cell exists. On connected uniformly gapped regions meeting the non-interacting plane $\lambda=0$, we prove a many-body gap-labeling theorem: the Hall conductivity appearing in the macroscopic Ohm's law is constant and quantized, satisfying $2\pi\sigma^{\mathrm{H}}\in\mathbb{Z}$. Thus the integer colors of the non-interacting Hofstadter butterfly persist as Hall-conductivity labels of interacting quantum Hall phases.

Quantum computing has seen multiple recent breakthroughs and is getting closer to demonstrations of an exponential advantage over classical computing for certain problems. Programmers will require high-level, general-purpose, executable programming languages to express quantum solutions clearly and effectively, and the field has already produced a wide variety of such languages. This paper presents a language classification framework and uses it to survey ten popular quantum programming languages. The findings include conceptual and experimental comparisons that result in a list of challenges for future language design.

In this work, we discuss how to determine and implement feasible optimal observables for a metrology protocol that saturates the quantum Fisher information (QFI) bound. In particular, we focus our study on a simple protocol, namely the method of moments (MoM). We first demonstrate that the symmetric logarithmic derivative (SLD) operator, a Hermitian observable, once implemented in the MoM, saturates the QFI bound. However, the SLD is generally too complex and typically non-local, rendering its direct experimental realization unfeasible. To overcome this limitation, we explore its structure in a specific sensing model - a Floquet time crystal (FTC) acting as an ac field sensor - and show that the SLD can be approximated by substantially simpler observables, such as the bare spin magnetization or a parity observable, for different relevant initial state preparations. We further corroborate our theoretical predictions in a nuclear magnetic resonance system operating as an FTC sensor, employing experimentally motivated parameters to simulate its performance in a state-of-the-art implementation. In general, our results establish a practical route toward near-optimal metrology in FTC sensors, where the inaccessible SLD operator can be replaced by simpler observables while retaining quantum-enhanced sensitivity.

All maximally entangled two-qubit states violate local realism with the same probability under uniformly random projective measurements, yet they need not behave identically in randomized Bell tests. We show that when measurement settings are exchanged between the parties in sequential Bell experiments, permutation symmetry of the shared state determines the statistical relation between the two realizations. Permutationally invariant states yield identical nonlocality outcomes in both experiments, whereas asymmetric states can violate local realism in one realization but not in the other. This distinction leads to two operational consequences. First, it enables the detection of correlations between the measurement choices of Alice and Bob through the joint violation statistics. Second, in Bell tests with finite measurement pools, asymmetric maximally entangled states can significantly increase the probability of observing nonlocality without requiring additional resources. Our results identify permutation asymmetry as a useful feature in randomized Bell experiments and highlight a new role of symmetry in quantum nonlocality.

What does it mean for a mixed-state topological phase to be chiral? Mathematically, chirality can be sharply characterized through the symmetry algebra of the mixed state. Physically, however, the question is far more subtle. In pure states, chirality in topological phase is tied to a web of familiar diagnostics, involving bulk-boundary correspondence, a gapless entanglement spectrum, a nontrivial modular commutator, and a quantized thermal Hall response. We show that none of these diagnostics remain reliable in mixed states. Instead, for decohered topological phases with a known error-free parent state, we propose two relative-entropy-based measures that can diagnose chirality, with one of them further extracting the chiral central charge. As a concrete example, we use these measures to analyze the $em^2$-decohered $\mathbb{Z}_3$ toric code, identifying the chirality transition to be in the random-bond Potts class for the particle-hole symmetric channel, and the polarized random bond Potts class for asymmetric channels. Our results emphasize how mixed-state topology demands intrinsically new diagnostics beyond direct analogues of pure-state probes.

Quantum annealers are supposed to follow adiabatically the ground state of a system as its Hamiltonian slowly interpolates between a trivial phase and a non-trivial one; the non-trivial ground state being the solution to an optimization problem. Overwhelmingly, their performances are measured in terms of how well or fast the optimization problem is solved. While pragmatic, this approach is inherently brittle as it strongly depends on the problem considered and the classical algorithm used as the reference benchmark. Here, we propose a quantity that not only measures the end result but also the quality of the actual quantum annealing process itself. Our metric is the quantum annealing counterpart of the fidelity-per gate of gate-based quantum computers. It takes the form of an accuracy $\epsilon$ for the equation of state of the annealer. We calculate benchmark values of $\epsilon$ using two variants of the simulated quantum annealing technique for Rydberg atoms systems. Our first approach uses variational quantum Monte-Carlo with an ansatz inspired by thermal annealing. It suggests that within $\epsilon \sim 10^{-2}-10^{-3}$, a quantum annealer is indistinguishable from its thermal classical counterpart. Critically, we could reach this precision up to $100,000,000$ atoms on a single CPU. Our second approach (based on Green function quantum Monte-Carlo) reaches accuracies around $\epsilon \sim 10^{-4}$ and we have run it up to $100,000$ atoms. These results outperform current Rydberg atom quantum annealing experimental platforms in both precision and size by orders of magnitude and put severe constraints for future hardware.

We introduce a framework of constructing topological subsystem codes based on the class of anticommuting quantum spin liquids described in [Phys. Rev. B 113, 064402 (2026)]. A canonical model from this class can be considered as a spatial modification of the toric code that voids its stabilizer code property. Rather, these models contain an extensive set of anticommuting local conserved operators that lead to an extensive ground state degeneracy. This degeneracy forms the basis of the subsystem degrees of freedom in the associated quantum error correcting code. The code inherits the many-body topological order of the quantum spin liquid, making it a topological subsystem code. We present two concrete and detailed examples for constructing these codes on a square lattice and a kagome lattice geometry, requiring weight-4 and weight-3 local check operator measurements respectively. In contrast to other subsystem codes, a unique property of these codes is the presence of an extensive number of local gauge qubits that are left undisturbed by the check operators apart from the logical qubits. Our construction provides a template for generating this new category of topological subsystem codes on different lattice or graph geometries, suitable for implementation on various quantum hardware platforms.