Papers

Quantum software testing (QST) checks whether quantum programs behave according to their intended specifications. A key requirement for QST research is a benchmark that supports rigorous empirical evaluation on programs that are testable and better reflect current software development practices. However, existing studies heavily rely on small hard-coded or circuit-level benchmarks, while available quantum programs are scattered across repositories without clear selection criteria, which limits fair comparison and systematic reproducibility. To this end, we present Qolumbina, a benchmark infrastructure for controlled QST experiments on scalable quantum programs. Qolumbina curates 40 programs from open-source repositories, turns them into test-ready subjects through systematic selection, refactoring, specifications, test case examples, unit tests, and standardized interfaces. We also propose QST-oriented criteria to characterize quantum programs along functionality, output behavior, development complexity, and quantum-specific execution complexity. Using these criteria, our empirical study shows that Qolumbina covers diverse testing-relevant properties and supports scalability analysis beyond fixed-size circuit benchmarks. Through controlled experiments with two recent QST approaches, we demonstrate the feasibility of using Qolumbina for execution-cost and fault-detection studies, and highlight backend-dependent effects that can influence QST result interpretation.

Mid-infrared quantum light sources hold broad application prospects in fields such as gas sensing and infrared thermal imaging. However, currently used mid-infrared quantum entangled light sources primarily rely on bulk periodically poled lithium niobate (PPLN) crystals, which limits brightness and integration. This paper proposes a theoretical scheme based on lithium niobate thin films, in which 1556.9 nm pumping is used to generate entangled photon pairs with a central wavelength of 3113.8 nm. By optimizing the waveguide structure and periodic polarization design, type-II phase matching and group velocity matching are achieved. This enables transverse electric (TE)-polarized pump input to be down converted to generate photon pairs with TE and transverse magnetic (TM) polarizations. Furthermore, by combining a domain arrangement algorithm used for the customized design of polarization direction in PPLN waveguides, precise phase matching is achieved, resulting in a quantum light source with a purity as high as 0.999 and a brightness of 6.18$\times 10^6$ cps/mW, which is three orders of magnitude higher than that of the bulk PPLN crystal source. This study provides a promising solution for realizing high-brightness, high-purity on-chip quantum light sources in the mid-infrared band.

It is necessary to investigate the local distinguishability of orthogonal quantum state sets, as their adoption in protocol design helps diminish quantum state transmission and cut operational costs. In this paper, we explore the local distinguishability of six orthogonal product states (OPSs) on any bipartite quantum system. We classify different sets of six bipartite OPSs into eight categories by using the vectors of the numbers of pairwise orthogonality relations, where any two states are orthogonal on only one subsystem within each set. We find that these eight categories contain a total of 78 distinct cases, all but five of which are perfectly distinguishable via local operations and classical communication (LOCC). Furthermore, we discuss the local distinguishability of those five distinct cases in detail. Our work explicitly characterizes the local distinguishability of six bipartite OPSs.

The aging transition is a critical phenomenon in which collective dynamics deteriorate as the fraction of inactive quantum nodes exceeds a threshold, referred to as the aging transition point. Such transitions are relevant to a broad range of biological and physiological systems, and may play an important role in quantum information processing, particularly in the stability assessment and robustness control of quantum networks. Detecting the aging transition point is therefore crucial for predicting network breakdown, since it marks the critical threshold at which a quantum network abruptly loses its stable active state and enters a degraded inactive phase. Here we propose a quantum sensing strategy to locate this transition point using a single qubit probe coherently coupled to a small subset of oscillator nodes. As the inactive fraction p approaches the aging transition point, the excited-state population of the probe becomes highly sensitive to variations in p, leading to a pronounced enhancement of the Fisher information. This critical enhancement enables high-precision estimation of the transition point. Remarkably, this enhancement survives even in the classical regime for the oscillators, where the Fisher information increases dramatically as p approaches the transition region. Our results establish a feasible route to sensing aging transitions in oscillator networks and provide a metrological perspective on critical phenomena in quantum many-body systems.

Rydberg-atomic receivers exhibit exceptional sensitivity yet are fundamentally constrained by the narrow instantaneous bandwidth, limiting their practical deployment in broadband scenarios. Prior approaches typically expand the bandwidth by physically broadening the atomic response, which usually requires auxiliary electromagnetic fields or stringent parameter tuning, thereby increasing overall system complexity. Here, we propose a compressive spectral multiplexing framework implemented in a waveguide-coupled Rydberg atomic receiver using a frequency-modulated local oscillator (FMLO). The FMLO creates multiple parallel sensing channels that collectively constitute a physical compressive sensing matrix, generating multiple narrowband intermediate-frequency replicas of the input signal. Thus, a broadband microwave spectrum is projected onto a set of narrowband atomic responses. It is demonstrated that spectral information spanning a bandwidth of over 640 MHz can be effectively compressed into the intrinsic atomic bandwidth of 126 kHz, achieving a spectrum compression ratio exceeding 1000. Furthermore, these output replicas offer intrinsic measurement redundancy and facilitate signal-to-noise ratio enhancement. An approximate 10 dB gain is achieved in the required bit-energy-to-noise-power-density ratio for multi-channel communication via maximal-ratio combining. This approach requires no auxiliary fields or broadband electronics, providing a simple and scalable pathway for chip-scale quantum receivers, latency-critical sensing, and next-generation wireless communications.

In the NISQ era, there is a need for resource-efficient proof-of-principle experiments that can be built up to genuine utility. Single-qubit classifiers (SQCs) are small-scale hybrid quantum-classical machines capable of performing a basic machine learning task: classifying data. In principle, these can be scaled up to many-qubit quantum classifiers capable of quantum computational advantage. Another type of quantum advantage is enabled by blind quantum computation (BQC), wherein a client may run delegated quantum computations on an untrusted server with information-theoretic security. In this paper, we develop a framework and propose a prototype experiment for a SQC where it is known to the server that a classification is being performed, but the data and outcome stay hidden, i.e., it performs partially-blind SQC (PB-SQC). This can be integrated into a quantum network to deliver quantum-secured classifications to remote clients; we study this for a heterogeneous quantum network link in which entanglement is shared between a server and a client equipped with a multiplexed solid-state quantum memory using entanglement swapping. The framework we develop for PB-SQC on this setup is tested in a simulation with realistic hardware parameters on a real-world credit card transaction fraud database with classification outcomes approaching those of its equivalent classical deep-belief network. In addition, we show how a two-qubit classifier (TQC) instead of a SQC enables verification of the computation. These results pave the way towards a short- to mid-term quantum network offering use-case-ready quantum applications.

False vacuum decay describes the relaxation of a metastable state through the nucleation and growth of bubbles of the stable phase. Despite describing a broad variety of phenomena across different fields, the quantum version of the nucleation theory has little experimental or numerical support. Testing its predictions is particularly important in two or more spatial dimensions, where bubble nucleation acquires its true geometrical nature. Here, we study false vacuum decay in the quantum Ising model in two dimensions. Through tree tensor network simulations we extract the decay rate, the effective interface tension and the critical bubble size. We compare them to new semi-classical field theory calculations, and find excellent agreement. These results provide numerical evidence that the critical-bubble picture survives in an interacting quantum spin system in 2+1 dimensions.

The security of practical quantum key distribution (QKD) systems is fundamentally constrained by vulnerabilities of single-photon detectors. Measurement-device-independent quantum key distribution (MDI-QKD) was proposed to remove this limitation by allowing all measurements to be performed by a completely untrusted party, under the assumption that the measurement node can be treated as adversarial but does not compromise the security guarantees of the protocol. Here we show that this assumption is insufficient under realistic adversarial control of the measurement device. We present an attack in which an adversary exploits active control of the measurement node (Charlie) to obtain significant information about the secret key. The attack enables recovery of up to 70% of the sifted key while introducing only 5.6% quantum bit error rate. Unlike previously reported attacks targeting specific implementations of MDI-QKD, our results demonstrate a limitation of the standard security model underlying the protocol. These findings indicate that additional constraints on the measurement-device independence assumption, or refined security analyses incorporating stronger adversarial capabilities, are required to ensure the security of MDI-QKD in realistic scenarios.

Quantum machine learning has recently emerged as a promising paradigm that leverages the expressive power of quantum circuits to address complex learning tasks. In this work, we investigate the applicability of hybrid quantum-classical neural networks to sentiment analysis, a central problem in natural language processing. We focus on a dataset of tweets related to COVID-19, where the textual content is vectorized using TF-IDF and fed into both classical feedforward networks and hybrid architectures incorporating parameterized quantum circuits. Our results show that hybrid models can achieve accuracy comparable to the classical baseline, while exhibiting distinct learning dynamics, especially in terms of validation loss and accuracy, that suggest a richer representational capacity. Moreover, when applying transfer learning to an SMS spam classification task, the hybrid models consistently outperform the classical counterpart, achieving an accuracy increase of 15 percentage points (from 66% to 81%) on the spam class, demonstrating enhanced generalization. These findings highlight the feasibility of employing QML for natural language processing and point toward the potential advantages of hybrid models as quantum hardware continues to advance.

Quantum magic is a fundamental resource that quantifies to what extent quantum states can be efficiently simulated on a classical computer. We study it for states constructed from the Sachdev-Ye-Kitaev (SYK) Hamiltonian with $N$ Majoranas by the fermionic anti-flatness (FAF). We show analytically that, in the large $N$ limit, the quantum magic of pure Kourkoulou-Maldacena (KM) states, dual to a quantum black hole with an end-of-world particle behind the horizon, is linear in $N$ with a slope, depending on the black hole temperature, that can be tuned between zero and $1/2$. By contrast, the FAF of Gaussian states evolved in real time with the SYK Hamitonian approaches $\approx N/2$ exponentially at a rate given by a multiple of the leading Ruelle-Pollicot resonance. Subleading corrections in $N$ for SYK energy eigenstates, computed numerically for $N \leq 54$ by combining Krylov subspace with GPU acceleration techniques, decay exponentially with $N$, but power-law if the SYK couplings are sparsified, and are order of magnitude larger for states close to the ground state, a region with an established gravity analogue. Our results offer new insights about the relation between quantum information, quantum chaos and low-dimension quantum gravity.

In this work, we investigate the generation of squeezed Schrödinger cat states in schemes based on photon-number-resolving measurements on multimode Gaussian states. We derive analytical expressions for the states generated in two- and three-mode schemes, as well as formulas for their fidelity with squeezed Schrödinger cat states. We analyze how the amplitude of the generated states scales with the number of detected particles. Furthermore, we derive an upper bound on the achievable generation fidelity and identify the conditions under which multimode schemes can enhance the quality of the generated states.

Long-lived logical qubits are essential for fault-tolerant quantum computation. However, the practical performance of traditional error correction protocols relies on performing specific syndrome circuits, causing vulnerability to hardware defects and imposing rigid connectivity constraints. Recent theoretical findings have proposed that flexible subroutine circuits within the LUCI framework can maintain space-time distance in the presence of isolated or broken components, albeit at the expense of temporal distance. However, these approaches have solely targeted defect avoidance and have not yet been demonstrated to suppress errors with reduced temporal distances on physical hardware. In this work, we propose a reset-free scenario for the LUCI framework and experimentally benchmark it on IBM quantum hardware. By asymmetrically scaling the $X$ or $Z$ distance, we compare our reset-free approach against the standard surface code and successfully demonstrate error suppression ratios for targeted logical Pauli errors. Remarkably, despite a nearly halved syndrome density in time, which requires two subroutine rounds for full syndrome extraction, the LUCI framework remains competitive with the rotated surface code implementation. In the LUCI framework, we observe error suppression of $1.75(10)$ for logical $X$ errors and $1.93(12)$ for logical $Z$ errors, whereas the standard approach yields $ 1.58(13)$ and $2.44(7)$, respectively. These results demonstrate that dynamic codes outperform standard methods by avoiding highly noisy components, even without physical defects, while preserving logical boundaries. Our findings challenge the conventional dependency on static fault-tolerant architectures by verifying the feasibility and efficacy of the LUCI framework on physical hardware and pave the way for hybrid, hardware-compatible code designs in quantum computing.

Typicality arguments for emergent spacetime rely on the Lubkin-Page bounds, which show that generic quantum states have vanishing correlations between subsystems. These bounds assume a tensor-product Hilbert space (a Type~I von~Neumann algebra), but the observable algebras in quantum field theory and quantum gravity are generically Type~II or Type~III, raising the question of whether the bounds survive. We prove that they do for all Type~II von~Neumann factors. For the hyperfinite Type~II$_1$ factor with a tripartite decomposition $R \cong A \otimes B \otimes E$, the mutual information between subsystems $A$ and $B$ vanishes as $O((d_A d_B / d_E)^2)$ in finite-dimensional approximations, provided $d_A d_B \leq d_E$ (Theorem~1). For Type~II$_\infty$ factors, including the gravitational algebras constructed via the crossed-product method by Witten and by Chandrasekaran, Longo, Penington, and Witten, the bound acquires an additional exponential suppression controlled by the Bekenstein-Hawking entropy (Theorem~2). We identify the obstructions to extending the result to Type~III factors and discuss the open question of whether the commutant of the observable algebra can serve as a natural thermal bath that tightens the bound further.

Block encodings are a basic interface between quantum algorithms and linear algebra. Standard LCU constructions achieve optimal circuit depth but typically require logarithmically many ancilla qubits. We ask how much quantum workspace can be reduced without sacrificing circuit depth, and study this tradeoff from both algorithmic and lower-bound perspectives. For a Hermitian decomposition $A=\sum_{j=1}^L \alpha_j H_j$, with $\|H_j\|=1$ and $\alpha=\sum_j|\alpha_j|$, we give two coherent $\varepsilon$-approximate block-encoding constructions. The first uses one ancilla qubit and has depth $\widetilde O(L(\alpha/\varepsilon)^{o(1)})$, while the second uses $O(\log\log(\alpha/\varepsilon))$ ancillas and achieves depth $\widetilde O(L)$. For a broad Suzuki-based coherent simulation architecture, we prove an ancilla-depth tradeoff. In the polynomial-resource regime and for a constant number of coherent rounds, $\log(1/\varepsilon)\le O((\log Q)^2+2^a\log Q)$, where $Q$ is depth normalized by the number of Hamiltonian terms and $a$ is the ancilla count. Thus polylogarithmic dependence on $1/\varepsilon$ requires more than constantly many ancillas within this architecture. In a separate repeated-query LCU model, for balanced coefficients $1/L$ and error $\varepsilon=\eta/L$ with fixed $0<\eta<1$, we prove $2^a=\Omega_\eta(L^2/(T+L))$, where $T$ is the number of oracle queries. Hence $a=\Omega(\log L)$ when $T=O(L^\alpha)$ for some $\alpha<2$. Moreover, in the exact case, $a\ge \log L$ regardless of $T$. We also extend this tradeoff to arbitrary nonnegative coefficients. Finally, we apply our low-ancilla constructions to normalized trace estimation in DQC1, obtaining an optimal algorithm linear in the approximate degree together with a matching query lower bound. Together, these results establish quantitative space-depth and space-query tradeoffs in two natural circuit models.

Memory devices for single photons are notable components for quantum information processing and quantum communications. The present study investigates the possibility of achieving storage of light at the level of single photons inside nanofibers by exploiting stimulated Brillouin scattering. We present first the standard approach using a coherent buffer in a nanoscale waveguide by transferring the optical signal coherently to an acoustic wave, and that can be extracted by the reverse process. The life time of the acoustic wave put limitation on the applicability of such approach for single photon signals. We introduce a configuration for achieving a slow signal at the level of single photons without gain or loss. The process utilizes photon-phonon Brillouin interactions involving two counter propagating pump fields. The photon storage is achieved through time delay of significantly slow signal inside nanowires. We address the condition for getting negligible influence due to the scattering off thermal phonons.

We establish an upper bound on extractable work for time-dependent, non-Markovian quantum heat engines operating with finite baths. This bound analytically isolates the distinct thermodynamic penalties arising from system-bath correlations, bath non-equilibrium, and residual interaction energy. Evaluating this framework operationally via a quantum polytropic cavity-optomechanical cycle, we demonstrate that maximal efficiency requires quasi-static operation to successfully harvest coherent, non-Markovian system-bath resonances. Conversely, optimising for maximum power enforces a strict finite-time regime. Under realistic hardware constraints, this acceleration necessitates larger discrete operational steps, where we expect Trotterisation errors to manifest as physical noise. Such noise would irreversibly suppress delicate quantum memory effects, forcing a collapse to the memoryless Markovian Otto limit. Coupled with the permanent energetic tax of switching finite-bath interactions, our results indicate that the exploitation of quantum memory resources and finite-power operation belong to different operational regimes.

Coherence-based spectroscopy methods are powerful tools to explore structure and dynamics of matter. However, towards higher photon energies, the generation of sequences of pulses with well-characterized relative delays and phases remains a challenge. Here, we introduce a method to measure the relative phase $\varphi$ between subsequent transform-limited pulses from high-repetition-rate x-ray free-electron lasers (XFELs). It is based on a Ramsey-type interference measurement, enabled by introducing long-lived Mössbauer resonances into the XFEL beam path up- or downstream a primary experiment, which allow one to bridge the temporal gap between the XFEL pulses. The measured phase can be used as additional input for the analysis of the primary experiment.

We study the compilation of structured quantum gate families on two-dimensional neutral-atom arrays, aiming to reduce addressing and transport overhead under realistic hardware constraints. For single-qubit gates, we exploit the algebraic structures of gate families at the matrix level, enabling efficient rank-one decompositions over appropriate algebraic structures and thereby reducing the number of addressing layers. For controlled-Z (C-Z) gates, we formulate the transport scheduling problem using graph-theoretic models, leading to efficient compilation algorithms under realistic transport constraints. We provide provable performance guarantees for the proposed methods and validate them through extensive numerical experiments. Across representative single-qubit gate families, our methods reduce the number of addressing layers by up to a factor of two compared with naïve row- or column-wise implementations. For C-Z gates, our scheduling strategy reduces the required number of atom transport operations by approximately 50%. When applied to QAOA circuits for MaxCut, the proposed framework reduces transport cost by more than 30% on average. These results show that the physical constraints of neutral-atom hardware can be converted into algebraic and graph-theoretic structure, turning a hardware-level scheduling bottleneck into tractable decomposition and coloring problems.

Glauber's coherent state is denoted by $\ket{\alpha}$ and its two-mode extension is represented by $\ket{\alpha,\beta}$. In this work, we introduce a two-mode superposition operator $A=tab+ra^\dagger b^\dagger$, whose action on the two-mode coherent state produces the two-mode coherent superposed quantum state $\ket{\psi}=(tab+ra^\dagger b^\dagger)\ket{\alpha,\beta}$. We investigate the nonclassicality and quantum non-Gaussianity of this state by means of the Wigner distribution and Wigner logarithmic negativity. Once its intrinsic nonclassical and non-Gaussian structure is established, the state is employed as the entangled resource in the Braunstein-Kimble continuous-variable (CV) teleportation protocol. We compute the ideal teleportation fidelity for coherent and squeezed inputs and analyze how the strengths of nonclassicality and non-Gaussianity influence the teleportation efficiency. Our results identify specific parameter regimes where enhanced non-Gaussian features or increased nonclassicality enable fidelities beyond the classical threshold, thereby revealing the operational significance of engineered two-mode quantum states in CV quantum information processing.

A common Morse Hamiltonian bridges the planar Kepler–Coulomb and hyperbolic Landau systems, linking flat electric dynamics to curved magnetic dynamics. A radial Liouville transformation with coupling-constant metamorphosis maps the separated Kepler problem to the Morse system, while fixed-horocyclic-momentum reduction maps the hyperbolic Landau problem to the same system. In a common normalization, the Coulomb coupling is the signed product of the magnetic field and conserved horocyclic momentum, while the quantum Landau reduction has the universal half-density shift $1/4$. Beyond this shared reduction, we construct a direct classical orbit map on the regular nonradial sectors for all signs of the Kepler energy. It maps the Landau height to a scaled inverse Kepler radius, Kepler ellipses, parabolas and hyperbolas to magnetic circles, horocycles and hypercycles, and Hamilton's hodograph affinely to the Landau carrier circle. The reduced Kepler symplectic form and the Binet-selected complex structure determine a Poincaré Kähler metric. Its nondegenerate Binet orbits have constant geodesic curvature of magnitude equal to the inverse eccentricity, while zero coupling gives geodesics. The orbit map identifies this metric isometrically with the Poincaré configuration-space metric of the hyperbolic Landau problem. Composing the quantum Liouville maps eliminates the Morse wavefunction and yields an exact weighted intertwining identity between the radial Kepler and horocyclic Landau operator pencils. At distinguished half-integer magnetic fields, the angular-momentum grading of a fixed Kepler shell is reorganized into the finite reduced Landau tower and its threshold endpoint. These exact correspondences hold in the stated reduced sectors despite the unitary inequivalence of the complete parent systems.

This study provides a theoretical expansion of the recent Data Relativistic Uncertainty (DRU) framework by formalizing a physics-to-AI paradigm for image enhancement. By modeling images as probabilistic wave functions rather than deterministic states, the paradigm explicitly integrates wave-particle duality to illustrate the system flow of how DRU leverages the intrinsic physical uncertainty of light, a dimension requiring further theoretical discussion. Consequently, this paradigm provides a rigorous Explainable AI (XAI) approach that enhances the interpretability of how DRU mitigates illumination bias and maintains robustness against data noise.

Quantum relative entropy is a core concept in physics, governing the limits of communication, thermodynamic irreversibility and quantum resource conversion. However, the requirement that physical processes cannot increase state distinguishability, the data-processing inequality, permits an infinite family of alternative divergence measures. Here we show that quantum relative entropy is uniquely selected by a sharper operational principle. We evaluate distinguishability through binary guessing games, in which an observer discriminates between pairs of quantum states using the optimal measurement. We prove that any additive measure that respects the odds revealed by these optimal measurements must coincide with the Umegaki relative entropy. This rigidity is a purely quantum phenomenon. Whereas classical theory permits a continuous family of valid divergence measures, including Rényi divergences, quantum noncommutativity. collapses this mathematical freedom. The result is exact, requiring neither a thermodynamic limit of infinitely many copies nor super-additivity assumptions for correlated states. It establishes quantum relative entropy not merely as an asymptotic quantity, but as the unique additive distinguishability measure compatible with single-shot quantum discrimination.

Bayesian quantum estimation offers a finite-data framework for quantum sensing and metrology, yet a unified geometric formulation for multiparameter Bayes risk has been lacking. We introduce Bayesian monotone metrics by evaluating Petz monotone metrics on the prior-averaged state, providing a Bayesian extension of the full class of statistically meaningful (CPTP) quantum metrics. This framework yields Bayesian quantities, including quantum posterior-mean operators and a quantum Bayesian dual Fisher-information matrix, and it leads to a systematic family of computable lower bounds on the Bayes risk. The resulting bounds naturally incorporate multiparameter measurement incompatibility and, for every monotone metric in the family, we prove a universal dominance over the corresponding quantum van Trees (Bayesian Cramér–Rao) bound. Moreover, we show that optimizing over all operator monotone functions collapses to a one-parameter subfamily, turning the tightest bound into a tractable optimization with a clear geometric interpretation. In representative examples, the optimized bounds are strictly tighter than the Bayesian SLD and RLD bounds. Our results establish Bayesian monotone metrics as a unifying information-geometric perspective on Bayesian quantum estimation, enabling systematic and computable performance limits in multiparameter settings.

The efficient preparation of correlated thermal states, such as the Thermofield Double (TFD) state, is a fundamental prerequisite for simulating quantum gravity models and many-body thermodynamics on quantum processors. In this work, we investigate the ground state preparation of the Two Coupled Sachdev-Ye-Kitaev model, known as the Maldacena-Qi model, which is dual to a traversable wormhole in $AdS_2$, utilizing feedback-based quantum algorithms. We demonstrate that the standard feedback-based quantum algorithm (FALQON) and its time-rescaled variant (TR-FALQON) face severe kinetic limitations in this system, failing to converge to the highly entangled ground state when initialized in trivial product states. To overcome these barriers, we propose the hybrid ITE-TR-FALQON protocol, which integrates the imaginary-time evolution present in imaginary-time-enhanced FALQON (ITE-FALQON) with the time-rescaling mechanism. Our numerical results indicate that the introduction of non-unitary dynamics is strictly necessary to break symmetry traps and filter out excited states, while time-rescaling drastically accelerates algorithm convergence. The proposed method achieves fidelities close to unity and reproduces the von Neumann and Rényi entropy spectra of the exact TFD state with high precision.

In this paper, we suggest a chiral interaction scheme to enhance magnon bundle emission by placing a qubit and a magnon into a cascaded-cavity setup, respectively. It is found that the unidirectional interaction prolongs the lifetime of the target excited state, thereby suppressing the magnon re-excitation and promoting both the average purity and number of two-magnon bundles. Consequently, the chiral interaction not only offers directional control but also improves the quality of the multi-magnon source, which may find potential applications in quantum information processing.

The quantum Kramers-Wannier (KW) duality is a fundamental transformation mapping short-range entangled (SRE) states to long-range entangled (LRE) states. While spatially local unitary circuits require linear-in-system-size depth to implement this duality, the ultimate speed limit for purely unitary circuits equipped with nonlocal connectivity remains an open question. Here, we explicitly construct logarithmic depth, spatially nonlocal unitary circuits that realize the exact $\mathbb{Z}_2$ KW dualities in both one and two spatial dimensions. We further generalize the construction to arbitrary $\mathbb{Z}_n$ KW dualities. Unlike algorithms tailored to prepare specific target states, our circuits implement complete duality maps. Within the symmetric (charge-neutral) sector, these dualities exactly transform arbitrary non-fixed-point SRE states into their corresponding LRE duals. Consequently, our results establish an efficient, purely coherent pathway for exploring phase transitions and topological dualities on modern quantum platforms.

We show that exchange symmetry in collisions of identical particles enables symmetry-protected coherent control of the total scattering cross section. For identical fermions, antisymmetrization enforces a common control phase among contributing channels within a given parity sector, yielding maximal control visibility. For identical bosons, phase-locking persists but with reduced visibility due to additional exchange (satellite) contributions. Collisions of distinguishable particles lack this symmetry-imposed phase-locking, leading to lower controllability and visibility. We elucidate these principles through coupled-channel quantum-scattering calculations for lithium-lithium collisions, comparing the $^{6}\mathrm{Li}{-}^{6}\mathrm{Li}$ (identical fermions), $^{7}\mathrm{Li}{-}^{7}\mathrm{Li}$ (identical bosons), and $^{6}\mathrm{Li}{-}^{7}\mathrm{Li}$ (distinguishable) systems. Furthermore, in the identical-particle cases, symmetry-enforced phase-locking enables full control over the parity of the final state even beyond the ultracold regime. This mechanism is broadly applicable to identical-particle collisions, including homonuclear molecules for which established approaches–DC electric fields or microwave shielding–are ineffective or unavailable.

All-optical (AO) microwave-free magnetometry using nitrogen-vacancy (NV) centers in diamond simplifies experimental design and broadens sample compatibility. While continuous-wave (cw) detection of AO photoluminescence (PL) changes is commonly employed, its performance is susceptible to systematic fluctuations such as optical intensity noise. To address these challenges, we introduce a pulsed AO protocol that employs two PL measurements within an optical pulse to suppress common-mode noise. At near-zero magnetic field, we experimentally demonstrate that the pulsed AO protocol resolves AO-PL contrast features arising from NV-NV cross-relaxation, achieving up to 10$\times$ improvement in the low-frequency noise floor compared to conventional cw AO techniques. We further investigate the dependence of AO-PL contrast on PL readout timing and the dark time duration $\tau$ between optical pulses, with the optimal $\tau$ varying based on NV concentrations. These findings provide insights into optimizing NV-diamond samples for effective AO operation across diverse applications.

Since the complexity of quantum state tomography (QST) scales exponentially with system size, exploiting priors such as low-rankness, tensor-network structures, and neural-network representations is essential for scalable QST in terms of sample complexity and parameter complexity. In this paper, we introduce a unified framework, termed structured factorization, that builds on BurerMonteiro-type factorization by parametrizing the density matrix as $FF^\dagger$, where the factor $F$ is constrained to belong to a structured model class. This factorization guarantees physical validity by construction while allowing a broad range of structural priors to be incorporated directly through the choice of the factor space, ranging from the generic Cholesky decomposition to low-rank matrices, matrix product operators, and neural density operators based on multilayer perceptron and transformer architectures. Building on this structured factorization framework, we formulate QST as an optimization problem over the factor space from measurement data. We first develop a unified statistical analysis of the sample complexity of least-squares estimation for a broad class of structured quantum states. We then propose a projected gradient descent method that operates directly on the factor space and accommodates a wide range of structural parametrizations and reconstruction objectives. To further exploit the geometry of the maximum-likelihood estimation formulation and the constraints on the factors, we derive a power method that yields a step-size-free algorithm with fast convergence, recovering Covers method as a special case when the factor is unconstrained.

Establishing quantum simulations as reliable tools for materials research requires quantitative validation against experiments and, where available, classical many-body calculations. For dynamical spin response, such validation remains challenging because experiment, classical simulation, and quantum simulation do not produce the same native observables. This challenge is increasingly relevant as quantum simulation protocols for dynamical response progress from theory to hardware-level benchmarking against neutron scattering data. The longer-term goal is to extend validation to classically intractable regimes accessible through future fault-tolerant implementations. Here, we develop a cross-pipeline validation framework for quantum simulation of dynamical spin response, using inelastic neutron scattering and classical many-body simulation as complementary experimental and computational anchors. The framework brings these pipelines to common momentum- and energy-resolved comparison levels through explicit forward and inverse observable maps, propagates uncertainty via covariance matrices or resampling, tests robustness to structured distortion, and evaluates agreement using a hierarchy of complementary metric families. It distinguishes stochastic uncertainty from robustness-induced distortion, carries both through the comparison chain, and uses the resulting metric-level uncertainty and distortion information to support layered validation at the pipeline, solver, and model levels. We also introduce actuator-aware feedback logic to improve agreement without obscuring the physical origin of any remaining mismatch. We close by outlining future extensions of this methodology, including upstream uncertainty and distortion modeling, adaptive feedback, asymmetric validation beyond full classical benchmarking, fault-tolerant workflows, and community infrastructure for reproducible validation.