Papers

Bell nonlocality is both a defining signature of entanglement and a key quantum information resource. However, visualizing and certifying nonlocal correlations across a spatially multimode photonic field remains challenging due to the rapidly growing measurement cost of spatially resolved projective tests. To address this issue, we build a spatial nonlocality imaging scheme that directly reveals the spatial distribution of quantum nonlocality by integrating a metasurface that performs parallel polarization projections with a quantum-adaptive neural network. Spatially resolved Clauser–Horne–Shimony–Holt (CHSH) tests are realized over a 400-pixel biphoton field using an average of only 1.7 detected coincidence pairs per pixel per basis. This approach yields a nonlocality image that maps the two-dimensional spatial distribution of Bell violations across the optical field and reveals the target-state-dependent spatial evolution of Bell violations. It provides a highly resource-efficient route to large-scale Bell certification and opens new possibilities for exploiting spatially multimode entanglement in quantum imaging, quantum networking, and scalable photonic quantum technologies.

Precision measurement of low-frequency electric field (LFEF) signals with frequency from 30 kHz to 300 kHz is crucial for advancing both fundamental science and practical applications, owing to their unique frequency regime. For conventional electromagnetic antennas, the long wavelength (i.e., several kilometers) of the LFEF leads to a severe size constraint that efficient radiation becomes challenging to achieve when the antenna size is much smaller than the long wavelength of the LFEF signals, which in turn results in a reduction of measurement sensitivity and compromises antenna's performance. By exploiting the high intrinsic sensitivity of cold trapped ions to weak alternating electric signals via Coulomb interaction, we demonstrate a single-ion phonon laser sensor acted by an injection-locked 40Ca+ ion confined in a surface-electrode trap. Combining the beat frequency technique with the injection-locked phonon laser oscillation, we demonstrate a practical and efficient approach for simultaneous extraction of the frequency, phase, and amplitude from a single measurement, without the need for sideband cooling. This approach achieves precision detection for LFEF signals with the sensitivity of 404 uV/(m * Hz1/2) and the detection limit of 61.5 uV/m. Besides, this approach also shows remarkable robustness against noise. Our study helps realizing practical single-atom sensors in the low-frequency regime, opening avenues for applications in subsurface communication, precision metrology, mass spectrometry, and biomedical monitoring.

Parametric frequency modulation is a standard tool in superconducting circuits for activating tunable interactions and implementing quantum gates. Here, we engineer dissipation in a flux-tunable transmon qubit by using sideband modulation to bring it into resonance with a lossy resonator, opening an on-demand Purcell decay channel. We find that pulsing this channel on and off does not simply lower the time-averaged decay rate; instead, it reorganizes the dissipation spectrum into a structured interference pattern. A Chebyshev-propagator model for the repeated on/off block reproduces the measured spectra and reveals a close structural correspondence to N-slit Fraunhofer diffraction, with each on-window acting as a temporal aperture. By varying the pulse duration and duty cycle, we demonstrate control over the spacing, contrast, and envelope of the dissipation spectrum. These results establish pulsed parametric modulation as a direct method for shaping engineered dissipation in superconducting circuits and provide a new control knob for open quantum system dynamics.

Mode connectivity has been widely studied in classical machine learning as a geometric property of low-loss regions in parameter space. In quantum machine learning (QML), however, the physically relevant object is not the parameter vector itself but the unitary transformation implemented by a parameterized quantum circuit. In this study, we formulate mode connectivity on the reachable unitary Lie group generated by the dynamical Lie algebra of the generators. We show that, under a near-minimum connectedness assumption and the absence of critical values in a low-loss band, the corresponding low-loss sublevel set on the reachable Lie group is path-connected. This provides a geometric interpretation of mode connectivity in QML that is independent of a particular parameterization. We further discuss how overparameterization can enable the lifting of Lie-group paths to parameter space, thereby making Lie-group connectivity observable in parameter-space experiments. Finally, we present toy numerical experiments in which geodesic interpolations between trained unitaries exhibit nearly zero loss barriers, consistent with the proposed interpretation.

Simulating the nonequilibrium dynamics of interacting open quantum systems remains challenging beyond small system sizes. Quantum phase-space representations provide a scalable approach, but their useful simulation time can be limited by broad distribution tails and the associated boundary terms. We introduce the neural gauge-$P$ representation for open bosonic systems, in which stochastic gauges are parameterized by neural networks and optimized using exact moment equation residuals. For the driven-dissipative Bose–Hubbard model in both single-site and square-lattice settings, the neural gauge-$P$ representation remains accurate during long-time evolution toward the steady state, whereas the corresponding ungauged representation becomes unreliable at substantially earlier times. These results demonstrate the potential of the neural gauge-$P$ representation for accurate simulations of nonequilibrium open quantum many-body dynamics.

Quantum optimal control (QOC) underpins adiabatic quantum computation, quantum annealing, and quantum state engineering, yet practical deployment is fundamentally bottlenecked by strict hardware constraints and substantial expert effort required to design protocols for each problem instance. To overcome this, we introduce QOC-Workbench, an auditable, large language model (LLM)-driven workflow that acts as an automated quantum co-scientist for cross-paradigm protocol design. Going beyond traditional numerical optimizers that merely tune parameters within a fixed formula, the LLM autonomously parses physics literature, proposes structural hypotheses, and writes code to validate them by direct simulation. This workflow supports cross-paradigm design by accumulating control motifs across tasks. We demonstrate this approach across three distinct settings: Case 1, Rydberg-atom maximum-independent-set arrays; Case 2, interacting XXZ spin chains; and Case 3, random transverse-field Ising models. In Cases 1 and 2, the workflow autonomously discovers hardware-compliant auxiliary controls, target catalysts, and schedule deformations that outperform literature baselines. In Case 3, it addresses the computational bottleneck of variational counterdiabatic driving by escalating from per-instance optimization to an amortized graph-neural-network generator, successfully transferring learned coefficient paths to larger unseen systems. By actively bridging the gap between theoretical algorithms and experimental restrictions across distinct control paradigms and Hamiltonian families, QOC-Workbench establishes a continuously evolving, cross-paradigm methodology for autonomous quantum control.

By applying the framework of entropic uncertainty relation (EUR) and the Quantum Leftover Hash Lemma (QLHL), we introduce a security-proof method for variable-length side-channel-secure (SCS) quantum key distribution (QKD) against coherent attacks. This method reframes composable security as a statistical fluctuation problem of phase errors, enabling direct proofs against coherent attacks through observables and virtual observables. It yields tight key rates for the SCS protocol and reduces pulse requirements by over two orders of magnitude compared to prior works that employ the post-selection technique. {Utilizing the characteristic of the SCS protocol that it has no untagged-bit bit-flip errors, we prove that the secure key length for the SCS protocol can be determined after Cascade error correction, using its actual parity disclosures. We also explain how the same argument extends to protocols with compatible bit-error-pattern and phase-error measurements.} We further identify sufficient conditions under which the final key length may be determined after error correction in a broader class of QKD protocols. Under the framework of EUR and QLHL, we clarify the applicability of several commonly used concentration bounds to variable-length QKD and the appropriate manner of their implementation. This work enhances the practical value of the SCS protocol and clarifies the security justification of key-rate formulas used in practical variable-length QKD implementations.

We develop a sparse operator-centric realization of $n$-qubit variational quantum algorithms in the complex Clifford algebra $\mathrm{Cl}(2n,\mathbb{C}) \cong M(2^n,\mathbb{C})$. Density operators, gates, observables, channels, fermionic modes, and adaptive-selection observables are represented in one Pauli-word algebra, with the Jordan–Wigner map providing the exact bridge to anticommuting Clifford generators. We distinguish general Pauli-word rotations from Spin-group rotors and formulate the familiar odd-$Y$ restriction for real-state adaptive ansatzes as an exact transpose-parity statement: for real Hamiltonians and real states, every candidate Pauli word containing an even number of $Y$ factors has zero ADAPT gradient, while odd-$Y$ rotations preserve the real sector. For the critical open transverse-field Ising chain, a depth-three Hamiltonian variational ansatz gives relative energy errors $4.84\times10^{-5}$, $2.19\times10^{-3}$, and $3.67\times10^{-3}$ for $n=4,5,6$. A compact local ADAPT pool is exact at $n=4$ but leaves residual errors at larger sizes; a systematic contiguous three-local odd-$Y$ pool reaches relative errors below $1.3\times10^{-12}$ for $n\leq6$. In 100-seed finite-shot tests at $n=4$, fixed-shot selection succeeds in $0/100$ runs, whereas uniform escalation and confidence-bound racing each succeed in $84/100$ runs; racing lowers median shots by $34\%$. We claim no asymptotic speedup over matrix methods. The contribution is a corrected algebraic formulation, a density-operator derivation and implementation of the real-sector pool filter, and a reproducible study of measurement-limited adaptive selection.

First-principles calculations are rarely single solver calls: they are multistage workflows in which structures, settings, and saved densities must pass correctly between dependent stages. Language models can write a valid single input, but reliability collapses once stages are chained: a dropped dependency, wrong file handoff, or hallucinated keyword can invalidate results even when the solver runs, and such errors surface only after costly execution. We introduce LatticeMind, a validation-gated agentic framework that converts natural-language requests into executable, checkable density functional theory (DFT) projects. A workflow contract specifies required stages, files, and dependencies; deterministic validators inspect the project before any solver launch; failed checks trigger bounded repair; and reports remain traceable to project files. On a 44-case RESCU benchmark spanning total-energy, density-of-states, band-structure, magnetic, phonon workflows, three non-flagship LLM backends reproduced every reference value; 119 of 132 runs passed on the first validated plan and the rest after one repair cycle. Ablations identify the workflow contract and pre-execution validation as the principal reliability mechanisms; a conventional trial-and-repair baseline reaches 71% at twice the token cost per success. The same architecture reproduces every reference value on a 19-case VASP benchmark, demonstrating transfer across solvers. Beyond these task families, LatticeMind generated and validated the 23 inputs of a multistage study of Rh-induced electronic responses at a Rh$_6$/In$_x$Ga$_{1-x}$N photocatalyst interface. These results establish workflow contracts, deterministic validation, bounded repair, and traceable records as a practical foundation for reliable AI-assisted scientific computing, where preventable errors are caught before execution and the solver is never the first validator.

We study the time-of-arrival (TOA) distribution of a Gaussian wave packet in the semiclassical regime for a general one-dimensional quadratic Hamiltonian, namely a forced harmonic oscillator with time-dependent frequency. Expanding the Gaussian probability density as a series in derivatives of the Dirac delta and using the standard rules for the composition of distributions with the classical trajectory, we obtain compact closed-form expressions for the leading semiclassical mean arrival time and its standard deviation. The mean acquires a quantum shift of order $\sigma^2$ set by the classical velocity and acceleration and by the time derivative of the Ermakov width, while the spread reduces to the simple form $\Delta\mathcal{T}_x\simeq\sigma(t_x)/v_x$. The latter implies a time–position uncertainty relation that depends only on the fundamental solutions of the classical equation of motion. We apply the framework to free fall and to two models of a time-dependent opening trap under gravity, and we validate every expression against exact numerical integration of the TOA distribution. These results extend earlier free-fall predictions to realistic settings in which the trapping potential cannot be neglected.

Non-Gaussian oscillator states are highly sensitive to weak perturbations, but reversible phase rotations and irreversible environmental changes should not be weighted equally. We introduce a finite-dimensional, direction-dependent local transport cost on a truncated Fock space and quotient it by Hamiltonian tangent directions. The resulting transverse quantity is a seminorm, not a global distance. A weighted operator frame specifies the representation cost of physical fluxes. Although the frame ({a_M,a_M^\dagger}) already spans the full trace-zero sector, multiphoton and diagonal directions can represent selected Lindblad tangents much more efficiently. Numerical tests on compass-like states show that phase rotations are removed, dephasing becomes inexpensive only after diagonal directions are included, and two- and three-photon processes are naturally captured by multiphoton frames. Thermal weights satisfy an operator-modular covariance but do not define a complete KMS geometry. The construction is therefore an environment-aware local diagnostic with explicit cutoff, regularization, and normalization conventions.

Wheeler's delayed-choice experiments and the time-symmetric formalisms of quantum measurement have long fueled a debate over whether time symmetry in quantum theory entails retrocausality. We argue that the debate conflates two distinct structures, and that the framework for separating them is the classical theory of conditioning: Doob $h$-transforms, Markov bridges, and enlargement of filtrations on the probabilistic side, and the forward-state/backward-effect (two-state-vector) formalism of pre- and post-selected systems on the quantum side. We sharpen Wheeler's participatory universe, delayed choice, and “It from Bit” into three theses and build a correspondence dictionary that maps each to a precise statement in one or both formalisms. The dictionary is anchored by two structurally isomorphic results: an operational proposition that a future measurement choice sorts the past ensemble into subensembles without disturbing any earlier marginal, and its classical counterpart, the disintegration of an unconditioned law into future-conditioned bridges – both a single fact: marginalizing over the final measurement leaves earlier marginals fixed, by completeness of the POVM together with trace preservation on the quantum side and by the tower property of conditional expectation on the classical. The conditional calculus is time-symmetric; its causal structure is not. Delayed choice is thereby a selection effect rather than retrocausation, and the apparent “pull from the future” is a bridge drift. We state explicitly what the framework does not do – it neither derives the Born rule nor solves the measurement problem – and delineate the legitimate scope of participatory language in quantum mechanics.

This work introduces a variant of Grover amplitude amplification using stabilizer and blade qubits to improve boosting robustness across objective distributions. We give geometric intuition, example simulations, and discuss limitations. Formal performance bounds and larger-scale validation are left for future research.

In this paper we derive the nonlocal Time-Energy uncertainty principle and then apply the published $^{229}$Th nuclear clock data as a first probe of the nonlocality scale \(E_M\). By using the direct clock-energy channel, we find conservative lower bounds on \(E_M\) at the tens of MeV scale, with optimistic present-data estimates reaching the hundred MeV scale. Including the known nuclear sensitivity enhancement of the $^{229}$Th transition gives us stronger model dependent bounds in the GeV range, while nuclear-scale reference-energy scenarios can reach the TeV range. The conclusion we draw from this is that nuclear clocks already provide an experimental route from nonlocal time–energy uncertainty to measurable laboratory bounds on non-Planckian nonlocality. We explore the idea of using a squeezed-state experiment with the $^{229}\mathrm{Th}$ nuclear clock to test the time–energy structure of nonlocal quantum field theory. The idea is reasonably obtainable within the near future of nuclear clock experiments. One would prepare an ensemble of thorium nuclei in a coherent superposition of the nuclear ground state and the low-lying isomeric clock state, entangle the participating nuclei through a collective interaction, and generate a family of spin-squeezed states with a tunable squeezing parameter $r$. Then a phase-controlled analysis pulse will rotate the selected collective nuclear quadrature into a measurable ground-isomer population difference. Near a strongly polarized collective state the normalized operators $J_y/\sqrt{S}$ and $J_z/\sqrt{S}$ obey the same approximate canonical algebra as the phase and amplitude quadratures of a squeezed optical mode. We use this experiment to either probe or bound the nonlocal energy scale $E_M$.

Language models are moving into chemistry and materials discovery workflows, where a wrong molecular formula, space group, or formation energy can silently propagate into downstream decisions. These confabulations hide inside fluent reasoning traces and concentrate on rare, long-tail entities, where model confidence is least trustworthy. Retrieving reference data for every prompt would catch them, but at a heavy coverage and abstention cost. We show that deterministic, database-grounded verification catches and repairs these errors selectively, and that the binding constraint is detection rather than repair. Our tiered verifier extracts each checkable claim, tests it against authoritative databases and physical law, and retrieves a reference value only when a check fails. Across four models and over five hundred prompts with pinned conditions, gated correction cuts the error rate of committed formulas from 22% to 4% with 3.2 times fewer retrievals than blanket augmentation, and it outperforms a conversational retrieval oracle when every answer, corrected or not, is scored. When a flag fires, repair almost always succeeds; the benefit reaches the final answer only where the verifier's scope covers it and where long-tail error exists. Checkable claims, checked cheaply, are a practical lever for trustworthy machine reasoning in chemistry.

Hilbert-space techniques are widely used not only for quantum theory, but also for classical physics. Two important examples are the Koopman-von Neumann (KvN) formulation and the method of “classical” wave functions. As this paper explains, these two approaches are conceptually distinct. In particular, the method of classical wave functions was not due to Bernard Koopman and John von Neumann, but was developed independently by a number of later researchers, perhaps first by Mario Schönberg, with key contributions from Angelo Loinger, Giacomo Della Riccia, Norbert Wiener, and E. C. George Sudarshan. The primary goals of this paper are to explain these two approaches, describe the relevant history in detail, and give credit where credit is due.

Polarization-encoded quantum communication requires compensation of polarization transformations induced by the optical links. If the compensator is embedded between two channel segments, the transformations before and after the compensator must be treated separately. Moreover, standard three-wave-plate polarization controllers can become non-universal when their retardances deviate from their ideal values. To address these two challenges, we introduce a four-wave plate compensator that synthesizes arbitrary SO(3) polarization transformations over a broad wavelength range, and an eight-Stokes vector protocol that reconstructs the two link-segment Mueller matrices on either side of the compensator. Our experiment reveals that the four-plate sequence suppresses polarization-induced excess quantum bit error rate (QBER) to the sub-percent level at an operating wavelength more than 100 nm from the design wavelength without further optimization. Combined with two auxiliary wavelengths, our scheme tracks the temperature-driven drift of a strongly wavelength-sensitive fiber spool while keeping the excess QBER below 1%. These results support flexible compensator placement and wavelength channel selection, as well as non-interruptive polarization control in wavelength-division-multiplexed quantum optical links.

We investigate colored $\Delta_T$ noise, i.e., finite-frequency $\Delta_T$ noise, as a probe of edge-mode (EM) transport in quantum Hall and quantum spin Hall systems. Colored $\Delta_T$ noise probes finite-frequency nonequilibrium current fluctuations and dynamical transport properties that are often obscured in DC measurements of conductance and noise. Since $\Delta_T$ noise is driven solely by a temperature and voltage bias under zero average charge current conditions, it eliminates current-induced Joule heating and directly probes intrinsic thermal fluctuations. We show that chiral, spin-conserving helical, and spin-flip helical (trivial) EMs exhibit distinct colored $\Delta_T$-noise signatures under appropriate bias protocols. Incorporating energy-dependent scattering through a quantum point contact, we demonstrate that electron-hole asymmetry significantly modifies the finite-frequency spectrum while preserving these distinguishing features. Notably, colored $\Delta_T$ noise exhibits a frequency-dependent sign reversal absent in the corresponding white ($\omega=0$) $\Delta_T$ noise. We further investigate zero-temperature colored quantum shot noise and find that it vanishes identically for chiral EMs, whereas the spin-conserving helical response changes sign with frequency. By contrast, spin-flip helical (trivial) EMs exhibit a positive colored shot-noise spectrum. However, the corresponding colored $\Delta_T$ noise retains its characteristic sign reversal, providing a robust distinction between spin-conserving helical and spin-flip helical (trivial) EM transport. These results establish colored $\Delta_T$ noise as a robust, experimentally accessible, complementary probe for identifying chiral, spin-conserving helical, and spin-flip helical (trivial) EM transport in mesoscopic topological systems.

Designing effective Lean proof agents is a central challenge in formal mathematical reasoning. Beyond building stronger provers, recent work emphasizes the workflow around Lean: how an agent decomposes proof obligations, uses tools and compiler feedback, diagnoses failures, repairs proofs, and maintains structured proof context. Motivated by code-level self-evolving agents, we study whether such workflows can be evolved rather than hand-designed. We present a self-evolving Lean proof agent in which a small fixed, trusted runtime wraps a fully mutable workspace: the proof workflow, prompts, and tools. Unlike most self-evolving systems, which optimize against a fixed external benchmark, our system coevolves the agent and its benchmark. Between generations, the highest-scoring agent (the champion) revises the active task distribution through a mastery-throttled curriculum update that introduces harder proof obligations only after the current level is mastered, and a single-anchor recalibration re-runs the champion on the updated benchmark to keep scores comparable as difficulty rises. All evolution stays inside a Lean-grounded verification loop: however the agent rewrites itself, a success counts only when its behavior yields Lean-verified proofs under a trusted snapshot, and each attempt must emit a machine-readable, Lean-grounded proof context whose representation may evolve but whose groundedness is enforced. We run the coevolving trajectory and a fixed-benchmark baseline for 15 active generations and compare them on a held-out miniF2F test split. The best coevolving agent reaches a 45.1% held-out solve rate, versus 12.7% for the seed and 32.0% for the best fixed-benchmark agent, showing that verifier-grounded self-evolution can improve Lean proof workflows under a coevolving benchmark.

We employ machine learning techniques to estimate the amount of information contained in three Krylov-space observables: the spread complexity $C(t)$, the discrete Wigner negativity $N(t)$, and the normalized negativity $\chi(t)=N(t)/|S(t)|$, where $S(t)$ is the survival amplitude. We study thermofield-double evolutions on GUE, GOE and Poisson spectra, and on the integrable $SL(2,R)$ Krylov chain of a two-dimensional CFT primary, with Lanczos coefficients $b_n=\alpha\sqrt{n(n+2h-1)}$. To introduce chaos we add a GUE random matrix to the integrable chain, $H(\varepsilon)=H_{SL(2,R)}+\varepsilon R_0 W_{GUE}$, where $R_0$ is its spectral half-width. Either $C(t)$ or $N(t)$ alone determines the thermofield temperature, with $R^2\simeq0.999$. However, neither can reconstruct the fine structure of the spectral form factor. In the integrable sector all three observables carry the same information. When we turn on chaos an asymmetry appears: $\chi$ predicts $C$ better than $C$ predicts $\chi$. This gap grows from $+0.33$ to $+0.77$, while the same gap for the raw negativity decays to zero. The extra information comes from the survival amplitude, and $\chi(t)$ carries it while $C(t)$ can still be recovered from $\chi(t)$. We derive a lower bound on this gap, set by the fraction of the variance of $\chi$ that comes from $S$.

Quasicrystals exhibit long-range positional order without periodicity, arising from multiple incommensurate wave vectors. In self-assembled quasicrystals, the spontaneous breaking of translational invariance gives rise to two Goldstone modes-phonons and phasons-associated with two competing wave vectors. Here, we demonstrate a unique scenario exclusive to quasicrystals: a mechanism that gaps out only one Goldstone mode (associated with one wave vector), while the other remains gapless. In one dimension, this leads to the coexistence of long-range order at the gapped wave vector and quasi-long-range order at the gapless one, due to sustained fluctuations. We show that this phenomenon can be realized using ultracold bosonic atoms in optical cavities.

Quantum machine learning models define probabilistic input–output maps through coherent quantum evolution and measurement. While such models can exhibit computational advantages, their internal functioning and decision making generally resists interpretation in terms of stochastic trajectories through intermediate configurations. In contrast to classical (Markovian) stochastic processes, quantum dynamics generically violates the Chapman–Kolmogorov divisibility condition, preventing a decomposition into probabilistically meaningful intermediate transitions. We develop a probabilistic framework for representing quantum learning models as stochastic processes over configuration spaces where the dynamics are modeled as linear maps on probability distributions. Starting from a fixed POVM, arbitrary quantum channels induce transition kernels on the associated probability representation. For informationally complete POVMs, and in particular SIC-POVMs, these kernels are Markovian but generally quasi-stochastic, with non-classicality appearing as negativity. By contrast, projective spaces admit positive stochastic kernels but generally require non-Markovian dynamics due to the failure of Chapman–Kolmogorov divisibility. This yields a trade-off between negativity and dependence on past configurations, i.e. quantum dynamics can be represented either by Markovian quasi-stochastic maps or by positive stochastic processes with higher Markov order. We discuss how such representations of quantum dynamics can be interpreted as stochastic walks through a memory space in the spirit of Projective Simulation, a model of learning and agency in which decisions arise from random walks over an episodic memory network. We further outline how finite-order stochastic kernels can approximate such quantum deliberation processes and show in what regimes the classical machine learning model is recovered.

Preserving the complex visibility of coherently captured starlight is essential for quantum-assisted long-baseline interferometry, because this nonlocal coherence carries the spatial information needed to form astronomical images. Yet finite memory lifetime and imperfect retrieval inevitably produce storage failures; when a failed cell is heralded, its erased subsystem can leak which-node information to the environment and dephase the stored coherence. Strict finite-dimensional (\(U(1)\)) covariance further forbids uniform exact correction of all single-memory erasures. We address this combined physical and symmetry-imposed limit using local number-conserving quantum scrambling, parameter-independent pattern-conditioned recovery, and a fixed Gottesman–Jennewein–Croke receiver. We prove a channel-to-Fisher-information stability theorem that converts approximate logical recovery into an operational guarantee on receiver-accessible information over compact visibility regions. All-pattern finite-size simulations show that scrambling redistributes erasure risk and suppresses high-leakage events, while a separate equal-budget comparison identifies a shallow design that outperforms the tested deeper and charge-sector Haar-random benchmarks at the prespecified operating point. A separate compilation resolves every nontrivial recovery branch into abstract nearest-neighbor number-conserving gates. Although the present low-rate design does not yet improve fixed-total-memory throughput, it establishes a blueprint for converting spare memory capacity into protection of astronomical coherence, opening a path toward higher-rate, erasure-resilient quantum telescope architectures.

Driven-dissipative quantum emitters provide a powerful platform for controllable excitation storage and release, with promising applications in quantum batteries and quantum storage. Yet, transient excitation transfer in collective many-body systems is often obscured by the intricate interplay among coherent driving, dissipation, and correlation dynamics. Here, we uncover a scalable excitation-storage mechanism in two emitter ensembles coupled to a semi-infinite waveguide. A coherently driven ensemble acts as an effective excitation reservoir, while a second ensemble positioned near a dissipative node serves as a subradiant storage medium. Surprisingly, when the driven ensemble largely exceeds the storage ensemble in size, the transfer dynamics enters a nearly correlation-free regime, allowing the driven ensemble to behave effectively as a classical excitation source. This reveals a simple scaling law for optimal excitation transfer, under which the storage ensemble approaches near-complete population inversion as the driven ensemble size increases. Building on this mechanism, we propose a three-stage storage-and-release protocol enabling fast excitation storage and controllable photon emission. Our results demonstrate how coherent and dissipative collective interactions can be jointly harnessed for quantum energy storage and programmable nonequilibrium dynamics in waveguide QED platforms.

Suppose that we encode quantum information into $ n $ physical carriers. With what probabilities can we perfectly recover the quantum information after sets of carriers have been erased? This question arises in the study of quantum erasure channels, for which M.B. Hastings conjectured that if each carrier is independently erased with probability $ t \geq 1/2 $, then it is impossible to recover the quantum information with asymptotically vanishing error and probability $ > 1-t $. We prove this conjecture by establishing new no-cloning constraints on realizable recovery probabilities.

Dissipation, though often detrimental to quantum entanglement, can be manipulated for the preparation of entangled states, wherein ingeniously designed quantum jump processes drive the system toward the desired steady state. Here we venture beyond this paradigm, and demonstrate a new type of entanglement generation in dissipative quantum dynamics. Combining driven-dissipative steady-state engineering and adiabatic passage, we propose a general protocol where the final entangled state depends on the chirality of the evolution path in the parameter space, a scheme that is further extendable to multipartite entanglement. By simulating the Liouvillian dynamics through the quantum Langevin equation for a pair of photons, we experimentally confirm the noise-resistant chiral preparation of various entangled states with high fidelity and concurrence. Our work establishes parametric chiral dynamics as a scalable and robust tool for controllable entanglement generation, paving the way for its applications in quantum information.

We review the truncated Wigner approximation (TWA) for spins as a computationally inexpensive numerical approximation method to describe interacting and / or dissipative many-body spin systems. Using the Wigner-Moyal mapping from Hilbert space to a suitable phase space, the many-body density matrix is represented by a c-number distribution, the Wigner function. The gauge freedom in continuous phase space can be exploited to find positive Wigner functions for a large class of spin states, including entangled ones. Employing different sets of correspondence rules, we derive equations of motion for the Wigner function, which, applying controlled approximations, can be mapped to stochastic differential equations. This allows a computationally inexpensive simulation of expectation values. Using a phase-space analog of the quantum regression theorem also multi-time correlations and spectra can be obtained. To illustrate the potential of the method, we benchmark the TWA for spins with some exactly solvable problems of interacting, dissipative spin systems, and then discuss its application to collective processes, such as the superradiant emission of light. Extending the TWA to imaginary time furthermore provides a tool to approximately calculate thermal and ground states of spin Hamiltonians. Finally, we show that the TWA stochastic equations can equivalently be derived within a path-integral approach, provided that the operator products in the dissipator are rigorously mapped onto the curved phase space.

Continuous time quantum walks built on graph Laplacians produce non monotonic graph propagation features through quantum interference during evolution, which classical diffusion cannot achieve. Such walks deliver a physically motivated propagation scheme for temporal graph signal modeling. We propose Quantum Walk Temporal Architecture (QWTA), which replaces classical graph propagation with a CTQW-type parameterized spectral propagator. QWTA embeds effective observation intervals into the spectral phase modulation of the propagation kernel. QWTA-Base preserves exact CTQW spectral evolution and serves as a physically faithful propagation reference. QWTA-GR further introduces phase soft clipping and gated residual fusion to stabilize propagation. The results show that explicit phase encoding of irregular time intervals, when combined with suitable stabilization, provides a physically motivated and competitive graph propagation design for temporal graph forecasting with missing historical observations.

Question-order effects in human survey data have been reported to approximately satisfy the QQ (quantum question) equality, a parameter-free prediction of the standard projective quantum question-order model. We develop this equality into an audit framework for sequential binary judgments of autoregressive large language models (LLMs). Theoretically, we characterize mechanism families that satisfy QQ robustly, show that classical repetition can reproduce the equality exactly, and combine QQ with the rank-2 Contextuality-by-Default criterion through $|q_{QQ}| \le \mathrm{OSS}$. This separates order sensitivity, QQ imbalance, and residual contextuality rather than treating them as interchangeable signatures. Methodologically, we introduce a committed multi-turn forced-branch protocol that reconstructs order-conditioned joint distributions from next-token log-probabilities under counterbalanced label mappings and pre-specified health gates. A first-signal pilot on an open-weight instruction-tuned model reveals the central measurement problem. Although all pre-specified health gates passed, the binary-conditioned distributions were near-deterministic for 17 of 18 item pairs under the direct-evaluation framing and 7 of 8 under the persona framing. Label assignment materially changed several mapping-specific QQ verdicts, and no item was certified as residually contextual. Thus, under the tested conditions, the observed QQ outcomes did not uniquely identify a response mechanism in the presence of a saturated and label-sensitive measurement interface. The main implication is methodological: next-token probabilities should not be interpreted as survey-response distributions without first establishing adequate dispersion. We therefore argue that saturation screening and label counterbalancing should precede structural interpretation in distribution-level audits of LLM judgments.

The interaction of an accelerated observer with a quantum field can modify the entanglement and quantum information shared between observers, thereby affecting quantum communication in non-inertial frames. We formulate the standard teleportation protocol in a relativistic setting where Alice remains inertial while Rob undergoes uniform acceleration and is modeled as an Unruh-DeWitt detector locally coupled to a massive scalar field. The detector-field interaction initially leads to a loss of entanglement and quantum information shared between Alice and Rob. Remarkably, under acceleration, the anti-Unruh regime can reverse this degradation, leading to an increase in both the shared entanglement and the accessible quantum information. We further find that, in the anti-Unruh regime, the teleportation fidelity is independent of the local free-evolution time of Alice's and Rob's states. At high accelerations, the recovered entanglement and quantum information enhance the teleportation fidelity, which approaches unity under appropriate conditions. These results demonstrate that the anti-Unruh effect can protect and recover quantum entanglement and information in a non-inertial frame by reducing the detector's effective temperature and the associated decoherence.