Papers

Airbridges are essential for creating high-performance, low-parasitic interconnects in integrated circuits and quantum devices. Conventional multi-step fabrication methods hinder miniaturization and introduce process-related defects. We report a simplified process for fabricating nanoscale airbridges using only a single electron-beam lithography step. By optimizing a multilayer resist stack with a triple-exposure-dose scheme and a thermal reflow step, we achieve smooth, suspended metallic bridges with sub-200-nm features that exhibit robust mechanical stability. Fabricated within a gradiometric SQUID design for superconducting transmon qubits, these airbridges introduce no measurable additional loss in the relaxation time $T_1$, while enabling a 2.5-fold enhancement of the dephasing time $T_2^*$. This efficient method offers a practical route toward integrating high-performance three-dimensional interconnects in advanced quantum and nano-electronic devices.

Efficient spectrum sharing in the Citizens Broadband Radio Service (CBRS) band is essential for maximizing 5G network capacity, particularly when high-traffic base stations require simultaneous access to multiple channels. Standard formulations of the Quantum Approximate Optimization Algorithm (QAOA) impose such multi-channel constraints using penalty terms, so most of the explored Hilbert space corresponds to invalid assignments. We propose a subspace-confined QAOA tailored to CBRS multi-channel allocation, in which each node-wise channel register is initialized in a Generalized Dicke state and evolved under an intra-register XY mixer. This ansatz confines the dynamics to a tensor product of Johnson graphs that exactly encode per-node Hamming-weight constraints. For an 8-node CBRS interference graph with 24 qubits, the effective search space is reduced from the full Hilbert space of size $2^{24}$ to 2916 feasible configurations. Within this subspace, the algorithm converges rapidly to low-conflict assignments without large penalty coefficients. Simulations on instances with up to eight nodes show that the proposed ansatz achieves near-optimal conflict levels and consistently outperforms standard penalty-based QAOA and a greedy classical heuristic in terms of feasibility. Noise simulations with depolarizing channels further indicate that the constraint-preserving structure maintains a high feasibility ratio in NISQ-relevant error regimes.

Background: Coronary angiography (CAG) is the cornerstone imaging modality for evaluating coronary artery stenosis and guiding interventional decision-making. However, interpretation based on single-frame angiographic images remains highly operator-dependent, and conventional deep learning models still face challenges in modeling complex vascular morphology and fine-grained texture patterns.Methods: We propose a Lightweight Quantum-Enhanced ResNet (LQER) for binary classification of coronary angiography images. A pretrained ResNet18 is employed as a classical feature extractor, while a parameterized quantum circuit (PQC) is introduced at the high-level semantic feature space for quantum feature enhancement. The quantum module utilizes data re-uploading and entanglement structures, followed by residual fusion with classical features, enabling end-to-end hybrid optimization with a strictly controlled number of qubits.Results: On an independent test set, the proposed LQER outperformed the classical ResNet18 baseline in accuracy, AUC, and F1-score, achieving a test accuracy exceeding 90%. The results demonstrate that lightweight quantum feature enhancement improves discrimination of positive lesions, particularly under class-imbalanced conditions.Conclusion: This study validates a practical hybrid quantum–classical learning paradigm for coronary angiography analysis, providing a feasible pathway for deploying quantum machine learning in medical imaging applications.

This article presents a concrete mathematical framework for the generation of entangled quantum states from classical stochastic processes. We demonstrate that any density operator $\rho_{AB}$ of a composite system can be derived from the correlations between two underlying stochastic processes, $X(t)$ and $Y(t)$, representing the random fluctuations of its subsystems. This construction utilizes a two-scale temporal scheme - micro and macro time - where quantum correlations emerge as macro-correlations derived from underlying micro-correlations. We propose the Double Covariance Model (DCM), which reproduces the some properties of quantum theory by treating quantum states as the fourth-order moment structure of an underlying classical probability space. DCM may also have potential implications for applications, particularly in quantum-inspired simulation and technology, and quantum-like modeling of cognition and decision making, as a tool for generation of density matrices with classical stochastic processes.

We demonstrate a substantial reduction in two-level system loss in tantalum coplanar waveguide resonators fabricated on high-resistivity silicon substrates through the use of an ultrathin titanium sacrificial layer. A 0.2nm titanium film, deposited atop pre-sputtered {\alpha}-tantalum, acts as a solid-state oxygen getter that chemically modifies the native Ta oxide at the metal-air interface. After device fabrication, the titanium layer is removed using buffered oxide etchant, leaving behind a chemically reduced Ta oxide surface. Subsequent high-vacuum annealing further suppresses two-level system loss. Resonators treated with this process exhibit internal quality factors Qi exceeding an average of 1.5 million in the single-photon regime across ten devices, over three times higher than otherwise identical devices lacking the titanium layer. These results highlight the critical role of interfacial oxide chemistry in superconducting loss and reinforce atomic-scale surface engineering as an effective approach to improving coherence in tantalum-based quantum circuits. The method is compatible with existing fabrication workflows applicable to tantalum films, offering a practical route to further extending T1 lifetimes in superconducting qubits.

Intrinsic randomness is generated when a quantum state is measured in any basis in which it is not diagonal. In an adversarial scenario, we quantify this randomness by the probability that a correlated eavesdropper could correctly guess the measurement outcomes. What if the eavesdropper is never wrong, but can sometimes return an inconclusive outcome? Inspired by analogous concepts in quantum state discrimination, we introduce the unambiguous randomness of a quantum state and measurement, and, relaxing the assumption of perfect accuracy, randomness with a fixed rate of inconclusive outcomes. We solve the maximal unambiguous randomness of any quantum state, optimised over all projective measurements, and find that it's proportional to the smallest eigenvalue of the state. We also solve both problems for any state and projective measurement in dimension two, and for an isotropically noisy state measured in an unbiased basis of any dimension. In the former case, when the setup is used to choose random bases for a prepare-and-measure quantum key distribution protocol, the unambiguous randomness quantifies the knowledge gained by an eavesdropper about the secret key, without causing any disturbance. In the latter, we find that, while experimental noise is typically ascribed to a single device, an eavesdropper correlated only to a noisy state is outperformed by an eavesdropper with joint correlations to both a noisy state and a noisy measurement. In fact, we identify a critical noise parameter beyond which the joint-noise eavesdropper achieves a perfect guessing probability, ending all hopes of private randomness.

As quantum technologies (QT) move from foundational research toward industrial and societal deployment, national strategies have become critical instruments for shaping the future of this emerging field. In this study, we conduct the first large-scale, data-driven analysis of 62 national quantum strategic documents (QSDs) from 20 countries. Using AI-based natural language processing (topic modeling), we identify 12 topics present in the text, ranging from technical development areas to transversal aspects such as workforce development and governance. Temporal analysis reveals a distinct shift in policy discourse toward applications of QT and commercialisation, and relatively away from basic science. Our findings highlight the increasing diversification of the QT field, and contribute to the growing area of quantum policy studies. We advocate for more AI and data-driven analyses of the quantum ecosystem, to work toward a scalable framework for understanding the technological and societal challenges of the second quantum revolution.

Neutral atoms have become a competitive platform for quantum metrology, simulation, sensing, and computing. Current magic trapping techniques are insufficient to engineer magic trapping conditions for qudits encoded in hyperfine states with $J \neq 0$, compromising qudit coherence. In this paper we propose a scheme to engineer magic trapping conditions for qudits via bichromatic tweezers. We show it is possible to suppress differential light shifts across all magnetic sublevels of the $5s5p$ $\mathrm{^{3}P_2}$ state by using two carefully chosen wavelengths (with comparable tensor light shift magnitude and opposite sign) at an appropriate intensity ratio, thus suppressing light-shift induced dephasing, enabling scalar magic conditions between the ground state and $5s5p$ $\mathrm{^{3}P_2}$, and tensor magic conditions for qudits encoded within it. Furthermore, this technique enables robust operation at the tensor magic angle 54.7$^\circ$ with linear trap polarization via reduced sensitivity to uncertainty in experimental parameters. We expect this technique to enable new loading protocols, enhance cooling efficiency, and enhance nuclear spins' coherence times, thus facilitating qudit-based quantum computing in ${}^{87}$Sr in the $5s5p$ $\mathrm{^{3}P_2}$ manifold.

Noise and errors are unavoidable in any realistic quantum process, including processes designed to reduce noise and errors in the first place. In particular, quantum thermodynamical protocols for cooling can be significantly affected, potentially altering both their performance and efficiency. Analytically characterizing the impact of such errors becomes increasingly challenging as the system size grows, particularly in deep quantum circuits where noise can accumulate in complex ways. To address this, we introduce a general framework for approximating the cumulative effect of gate-dependent noise using a global depolarizing channel. We specify the regime in which this approximation provides a reliable description of the noisy dynamics. Applying our framework to the thermodynamical two-sort algorithmic cooling (TSAC) protocol, we analytically derive its asymptotic cooling limit in the presence of noise. Using the cooling limit, the optimal cooling performance is achieved by a finite number of qubits–distinguished from the conventional noiseless TSAC protocol by an infinite number of qubits–and fundamental bounds on the achievable ground-state population are derived. This approach opens new avenues for exploring noisy quantum thermodynamical processes.

We derive a modified Lindblad equation for the state of quantum dot tunnel coupled to a Markovian lead when the spin state of the dot is driven by an oscillating magnetic field. We show that the equation is a completely positive, trace-preserving map and find the jump operators. This is a driven-dissipative regime in which coherent driving is relevant to the tunneling and cannot be treated as simply a rotation modifying the system with a bath derived under a static magnetic field. This work was motivated by an experimental desire to determine the Zeeman splitting of an electron spin on a quantum dot (a spin qubit), and in a related work we show that this splitting energy can be found by measuring the charge occupancy of the dot while sweeping the frequency of the driving field \ arXiv:2503.17481. Here we cover the full derivation of the equation and give the jump operators. These jump operators are potentially useful for describing the stochastic behavior of more complex systems with coherent driving of a spin capable of tunneling on or off of a device, such as in electron spin resonance scanning tunneling microscopy. The jump operators have the interesting feature of combining jumps of electrons onto and off of the device.

The (pion) decays controlled by axial anomaly imply the specific entanglement between photons having also the counterparts for classical electromagnetic waves. This is also a specific case of Eisnstein-Podolsky-Rosen-Bohm-Aharonov effect. The absence of causality and non-locality in (angular) momentum conservation is manifested, being especially clear for the generalization to the case of time rather than space separation corresponds to the polarization of dileptons described by time-like pion transition formfactors which may be studied experimentally. The similar decays in external magnetic field manifest the interplay with vacuum conductivity in external magnetic field and longitudinal polarization of vector mesons observed in heavy-ion collisions.

We establish anisotropic uncertainty principles (UPs) for general metaplectic operators acting on $L^2(\mathbb{R}^d)$, including degenerate cases associated with symplectic matrices whose $B$-block has nontrivial kernel. In this setting, uncertainty phenomena are shown to be intrinsically directional and confined to an effective phase-space dimension given by $\mathrm{rank}(B)$. First, we prove sharp Heisenberg-Pauli-Weyl type inequalities involving only the directions corresponding to $\ker(B)^\perp$, with explicit lower bounds expressed in terms of geometric quantities associated with the underlying symplectic transformation. We also provide a complete characterization of all extremizers, which turn out to be partially Gaussian functions with free behavior along the null directions of $B$. Building on this framework, we extend the Beurling-Hörmander theorem to the metaplectic setting, obtaining a precise polynomial-Gaussian structure for functions satisfying suitable exponential integrability conditions involving both $f$ and its metaplectic transform. Finally, we prove a Morgan-type (or Gel'fand–Shilov type) uncertainty principle for metaplectic operators, identifying a sharp threshold separating triviality from density of admissible functions and showing that this threshold is invariant under metaplectic transformations. Our results recover the classical Fourier case and free metaplectic transformations as special instances, and reveal the geometric and anisotropic nature of uncertainty principles in the presence of symplectic degeneracies.

Conformal field theories (CFTs) feature prominently in high-energy physics, statistical mechanics, and condensed matter. For example, CFTs govern emergent universal properties of systems tuned to quantum phase transitions, including their entanglement, correlations, and low-energy excitation spectra. Much of the rich structure predicted by CFTs nevertheless remains unobserved in experiment. Here we directly observe the energy excitation spectra of emergent CFTs at quantum phase transitions – recovering universal energy ratios characteristic of the underlying field theories. Specifically, we develop and implement a modulation technique to resolve a Rydberg chain's finite-size spectra, variably tuned to quantum phase transitions described by either Ising or tricritical Ising CFTs. We also employ local control to distinguish parities of excitations under reflection and, in the tricritical Ising chain, to induce transitions between distinct CFT spectra associated with changing boundary conditions. By utilizing a variant of the modulation technique, we furthermore study the dynamical structure factor of the critical system, which is closely related to the correlation of an underlying Ising conformal field. Our work not only probes the emergence of CFT features in a quantum simulator, but also provides a technique for diagnosing a priori unknown universality classes in future experiments.

We combined experimental and theoretical investigations of an effective two-level atomic system operating in the near-infrared telecom wavelength regime, realized using hot rubidium vapor confined within a sub-micron-thick cell. In this strongly confined geometry, atomic coherence is profoundly influenced by wall-induced relaxation arising from frequent atom-surface collisions. By analyzing both absorption and fluorescence spectra, we demonstrate that the optical response is dominated by a closed cycling transition, which effectively isolates the atomic dynamics to a two-level configuration despite the presence of multiple hyperfine states. This confinement-induced selection suppresses optical pumping into uncoupled states and enables robust, controllable light-matter interaction at telecom wavelengths within a miniature atomic platform. Our results establish a practical route to realizing near-infrared atomic two-level systems in compact vapor-cell devices, opening new opportunities for integrated quantum photonic technologies, including on-chip quantum memories, telecom-band frequency references, and scalable quantum information processing.

Informationally overcomplete POVMs are known to outperform minimally complete measurements in many tomography and estimation tasks, and they also leave a purely classical freedom in shadow tomography: the same observable admits infinitely many unbiased linear reconstructions from identical measurement data. We formulate the choice of reconstruction coefficients as a convex minimax problem and give an algorithm with guaranteed convergence that returns the tightest state-independent variance bound achievable by post-processing for a fixed POVM and observable. Numerical examples show that the resulting estimators can dramatically reduce sampling complexity relative to standard (canonical) reconstructions, and can even improve the qualitative scaling with system size for structured noncommuting targets.

Non-adiabatic dynamics at molecule-metal interfaces govern diverse and technologically important phenomena, from heterogeneous catalysis to dye-sensitized solar energy conversion and charge transport across molecular junctions. Realistic modeling of such dynamics necessitates taking into account various charge and energy transfer channels involving the coupling of nuclear motion with a very large number of electronic states, leading to prohibitive cost using classical computational methods. In this work we introduce a generalization of the Anderson-Newns Hamiltonian and develop a highly optimized quantum algorithm for simulating the non-adiabatic dynamics of realistic molecule-metal interfaces. Using the PennyLane software platform, we perform resource estimations of our algorithm, showing its remarkably low implementation cost for model systems representative of various scientifically and industrially relevant molecule-metal systems. Specifically, we find that time evolution for models including $100$ metal orbitals, $8$ molecular orbitals, and $20$ nuclear degrees of freedom, requires only $271$ qubits and $7.9 \times 10^7$ Toffoli gates for $1000$ Trotter steps, suggesting non-adiabatic molecule-metal dynamics as a fruitful application of first-generation fault-tolerant quantum computers.

The Superconducting Quasiparticle-Amplifying Transmon (SQUAT) is a new sensor architecture for THz (meV) detection based on a weakly charge-sensitive transmon directly coupled to a transmission line. In such devices, energy depositions break Cooper pairs in the qubit capacitor islands, generating quasiparticles. Quasiparticles that tunnel across the Josephson junction change the transmon qubit parity, generating a measurable signal. In this paper, we present the design of first-generation SQUATs and demonstrate an architecture validation. We summarize initial characterization measurements made with prototype devices, comment on background sources that influence the observed parity-switching rate, and present experimental results showing simultaneous detection of charge and quasiparticle signals using aluminum-based SQUATs.

Multipartite entanglement is a natural generalization of bipartite entanglement, but is relatively poorly understood. In this paper, we develop tools to calculate a class of multipartite entanglement measures - known as multi-invariants - for stabilizer states. We give an efficient numerical algorithm that computes multi-invariants for stabilizer states. For tripartite stabilizer states, we also obtain an explicit formula for any multi-invariant using the GHZ-extraction theorem. We then present a counting argument that calculates any Coxeter multi-invariant of a q-partite stabilizer state. We conjecture a closed form expression for the same. We uncover hints of an interesting connection between multi-invariants, stabilizer states and topology. We show how our formulas are further simplified for a restricted class of stabilizer states that appear as ground states of interesting models like the toric code and the X-cube model.

As quantum devices scale to larger and larger sizes, a significant challenge emerges in scaling their coherent controls accordingly. Quantum cellular automata (QCAs) constitute a promising framework that bypasses this control problem: universal dynamics can be achieved using only a static qubit array and global control operations. Despite an extensive history of theoretical explorations and proposals, QCAs have not been experimentally explored in the context of highly-scalable globally-controlled systems. Here we realize QCAs on a dual-species Rydberg array of rubidium and cesium atoms, leveraging independent global control of each species to perform multiple quantum protocols. Seeding an automaton with different initial states, we explore many-body dynamics of quasiparticles and grow GHZ states across both species, highlighting the flexibility of our approach. We further develop a second automaton using a novel mediated entangling gate, enabling generation of 96.7(1.7)%-fidelity Bell states, 17-qubit cluster states, and high-connectivity graph states. Our results demonstrate that simple global controls enable access to a rich variety of applications through the QCA framework. The versatility and scalability of QCAs present compelling opportunities for the development of quantum information systems, as well as new perspectives on quantum many-body dynamics.

Fault-tolerant quantum computation in photonic architectures requires efficient preparation of high-fidelity logical magic states under realistic constraints of finite squeezing and photon loss. We present LiDMaS (Lightweight Density-Matrix Simulator), an architecture-level study of logical $T$-gate magic-state preparation in Gottesman–Kitaev–Preskill (GKP)-encoded photonic qubits using a repeat-until-success (RUS) injection protocol combined with outer surface-code protection. A density-matrix simulator based on standard numerical linear algebra is employed, mapping finite squeezing to effective logical dephasing, incorporating logical depolarizing noise, and treating photon loss as a heralded erasure process. Parameter sweeps are performed over squeezing values from $8$ to $16$~dB, baseline loss probabilities between $0.005$ and $0.03$, and surface-code distances $d=1,3,5,$ and $7$. Across this regime, RUS success probabilities range from about $0.90$ to $0.99$, with average injection overhead between $1.15$ and $1.21$ rounds per successful attempt. After outer-code protection, logical fidelities reach $F_{\mathrm{log}} \approx 0.765\text{--}0.796$, exhibiting weak sensitivity to moderate photon loss but strong monotonic dependence on squeezing. Sensitivity analysis identifies finite squeezing as the dominant continuous error source, while loss primarily impacts heralded failure rates. Phase-boundary diagrams determine minimum squeezing requirements to achieve success probability $\ge 0.95$ and logical fidelity $\ge 0.79$ as a function of code distance, providing quantitative design guidance for scalable photonic fault-tolerant architectures.

Bell tests based on homodyne detection are strongly constrained in continuous-variable systems. Can Gottesman-Kitaev-Preskill (GKP) encoding turn homodyne detection into a practical tool for revealing Bell nonlocality? We consider a physically motivated model in which each party performs homodyne detection and digitizes the continuous outcome via a fixed periodic binning, corresponding to logical Pauli measurements. Within this framework, we derive a bipartite no-go: CHSH cannot be violated for Bell-pair states. Moving beyond two parties, we show that finitely squeezed GKP-encoded GHZ and W states nevertheless exhibit strong multipartite nonlocality, violating multipartite Bell inequalities with homodyne-only readout. We quantify the required squeezing thresholds and robustness to loss, providing a route toward homodyne-based Bell tests in continuous-variable systems.

Probing energy-dependent transport in quantum simulators requires preparing states with tunable energy and small energy variance. Existing approaches often study quench dynamics of simple initial states, such as computational basis states, which are far from energy eigenstates and therefore limit the achievable energy resolution. In this work, we propose using wavepackets to probe transport properties with improved energy resolution. To demonstrate the utility of this approach, we prepare and evolve wavepackets on Quantinuum's H2-2 quantum computer and identify an energy-dependent localization transition in the Anderson model on an 8x7 lattice–a finite-size mobility edge. We observe that a wavepacket initialized at low energy remains spatially localized under time evolution, while a high-energy wavepacket delocalizes, consistent with the presence of a mobility edge. Crucial to our experiments is an error mitigation strategy that infers the noiseless output bit string distribution using maximum-likelihood estimation. Compared to post-selection, this method removes systematic errors and reduces statistical uncertainty by up to a factor of 5. We extend our methods to the many-particle regime by developing a quantum algorithm for preparing quasiparticle wavepackets in a one-dimensional model of interacting fermions. This technique has modest quantum resource requirements, making wavepacket-based studies of transport in many-body systems a promising application for near-term quantum computers.

Understanding how microscopic few-body interactions give rise to thermal behavior in isolated quantum many-body systems remains a central challenge in nonequilibrium statistical mechanics. While individual energy eigenstates are expected to reproduce thermal equilibrium values, analytic access to highly entangled thermal eigenstates of nonintegrable Hamiltonians remains scarce. In this Letter, we construct exact infinite-temperature eigenstates of generically nonintegrable two-body Hamiltonians using stabilizer states. These states can fully reproduce thermal expectation values for all spatially local observables, extending previously known Bell-pair-based constructions to a broader class. At the same time, we prove a sharp no-go theorem: stabilizer eigenstates of two-body Hamiltonians cannot satisfy microscopic thermal equilibrium for all four-body observables. This bound is tight, as we explicitly construct a translationally invariant Hamiltonian whose stabilizer eigenstate is thermal for all two-body and three-body observables as well as all spatially local observables. Our results suggest that reproducing higher-order thermal correlations requires nonstabilizer degrees of freedom, providing analytic insight into the interplay between interaction locality, microscopic thermal equilibrium, and quantum computational complexity.

At the heart of quark confinement and hadronization, the physics of flux strings has recently become a focal point in the field of quantum simulation of high-energy physics (HEP). Despite considerable progress, a detailed understanding of the behavior of flux strings in quantum simulation-relevant lattice formulations of gauge theories has remained limited to the lowest truncations of the gauge field, which are severely limited in their ability to draw conclusions about the quantum field theory limit. Here, we employ tensor network simulations to investigate the behavior of flux strings in a quantum link formulation of $2+1$D quantum electrodynamics (QED) with a spin-$1$ representation of the gauge field. We first map out the ground-state phase diagram of this model in the presence of two spatially separated static charges, revealing distinct microscopic processes responsible for string breaking, including a two-stage breaking mechanism not possible in the spin-$\frac{1}{2}$ formulation. Starting in different initial product state string configurations, we then explore far-from-equilibrium quench dynamics across various parameter regimes, demonstrating genuine $2+1$D real-time string breaking and glueball-like bound state formation, with the latter not possible in the spin-$\frac{1}{2}$ formulation. In and out of equilibrium, we consider different values and placements of the static charges. Finally, we provide efficient qudit circuits for a quantum simulation experiment in which our results can be observed in state-of-the-art ion-trap setups. Our findings lay the groundwork for quantum simulations of flux strings towards the quantum field theory limit.

We present a method for associating labeled directed graphs to finite-dimensional Lie algebras that are $graph$-$admissible$. The proposed framework enables visual identification of key structural algebraic features. We first formalize this approach and establish several classes of Lie algebras that admit the categorization as graph-admissible Lie algebras, and then investigate suitable valid graphs for this approach by translating the antisymmetry of the Lie bracket and the Jacobi identity into rules that such graphs must satisfy. Furthermore, based on these foundations, we provide graph-theoretic criteria for solvability, nilpotency, presence of ideals, simplicity, semisimplicity, and reductiveness of an algebra. We also present practical algorithms for constructing such graphs and those associated with the lower central series and derived series via iterative pruning procedures. We further cover specific examples, such as the Schrödinger and Lorentz algebras, which illustrate the applicability of the developed tools to physically relevant cases. Moreover, we explore applications in physics, where the method facilitates computation of similarity transformations essential for determining quantum mechanical time evolution via the Lie-algebraic factorization method. We also discuss a possible generalization of the framework based on magma-gradings of Lie algebras and formulate related open questions. Our approach bridges algebraic and combinatorial perspectives, offering theoretical tools for this area of mathematical physics.

Many physical phenomena, including thermalization in open quantum systems and quantum Gibbs sampling, are modeled by Lindbladians approximating a system weakly coupled to a bath. Understanding the convergence speed of these Lindbladians to their steady states is crucial for bounding algorithmic runtimes and thermalization timescales. We study two such families of processes: one characterizing a repeated-interaction Gibbs sampling algorithm, and another modeling open many-body quantum thermalization. We prove that both converge in polynomial time for several non-commuting systems, including high-temperature local lattices, weakly interacting fermions, and 1D spin chains. These results demonstrate that simple dissipative quantum algorithms can prepare complex Gibbs states and that Lindblad dynamics accurately capture thermal relaxation. Our proofs rely on a novel technical result that extrapolates spectral gap lower bounds from quasi-local Lindbladians to the non-local generators governing these dynamics.

In combinatorial optimization problems with degenerate ground states, fair sampling of degenerate solutions is essential. However, the quantum approximate optimization algorithm (QAOA) with a standard transverse-field mixer induces biases among degenerate states as circuit depth increases. Based on quantum-classical correspondence theory, we propose SBO-QAOA, which employs a temperature-dependent Hamiltonian encoding a Gibbs distribution as its ground state. Numerical simulations show that, unlike standard QAOA, SBO-QAOA yields ground-state probabilities converging to finite-temperature values with uniform distribution among degenerate states. These fairness and temperature-targeting properties are preserved even with only four variational parameters under a linear schedule.

We introduce a class of pseudo-bosonic Klein-Gordon fields in 1+1 dimensions and we discuss some of their properties. This work originates from non Hermitian quantum mechanics and deformed canonical commutation relations. We show that, within this class of fields, there exist a specific subclass with the interesting feature of having finite equal space-time two-points function, contrarily to what happens for standard Klein-Gordon fields. This, in our opinion, is a relevant aspect of our proposal which is a good motivation to undertake a deeper analysis of this (and related) quantum fields.

Hidden Markov models (HMMs) are ubiquitous in time-series modelling, with applications ranging from chemical reaction modelling to speech recognition. These HMMs are often large, with high-dimensional memories. A recently-proposed application of quantum technologies is to execute quantum analogues of HMMs. Such quantum HMMs (QHMMs) are strictly more expressive than their classical counterparts, enabling the construction of more parsimonious models of stochastic processes. However, state-of-the-art techniques for QHMM compression, based on tensor networks, are only applicable for a restricted subset of HMMs, where the transitions are deterministic. In this work we introduce a pipeline by which any finite, ergodic HMM can be compressed in this manner, providing a route for effective quantum dimension reduction of general HMMs. We demonstrate the method on both a simple toy model, and on a speech-derived HMM trained from data, obtaining favourable memory–accuracy trade-offs in the examples studied, relative to a simple classical state-merging baseline.

Real-time decoding of quantum error correction (QEC) is essential for enabling fault-tolerant quantum computation. A practical decoder must operate with high accuracy at low latency, while remaining robust to spatial and temporal variations in hardware noise. We introduce a hardware-conditioned neural decoder framework designed to exploit the natural separation of timescales in superconducting processors, where calibration drifts occur over hours while error correction requires microsecond-scale responses. By processing calibration data through a graph-based encoder and conditioning a lightweight convolutional backbone via feature-wise linear modulation (FiLM), we decouple the heavy processing of device statistics from the low-latency syndrome decoding. We evaluate this approach using the 1D repetition code as a testbed on IBM Fez, Kingston, and Pittsburgh processors, collecting over 2.7 million experimental shots spanning distances up to d = 11. We demonstrate that a single trained model generalizes to unseen qubit chains and new calibration data acquired days later without retraining. On these unseen experiments, the FiLM-conditioned decoder achieves up to an 11.1x reduction in logical error rate relative to modified minimum-weight perfect matching. We observe that by employing a network architecture that exploits the highly asynchronous nature of system calibration and decoding, hardware-conditioned neural decoding demonstrates promising, adaptive performance with negligible latency overhead relative to unconditioned baselines.