Quantum Physics
Selective Placement of Hollow-Core Fibers for QKD and Classical Communication Coexistence
Giovanni Simone Sticca, Alessandro Gagliano, Memedhe Ibrahimi et al. (+3 more)
We investigate the benefits of partially upgrading optical networks with hollow-core fibers for QKD-classical communication coexistence. Results show that upgrading 40% of links in a metro
topology can reduce the number of
quantum modules by up to 49%.
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All authors Giovanni Simone Sticca, Alessandro Gagliano, Memedhe Ibrahimi, Alberto Gatto, Francesco Musumeci, Massimo Tornatore
Quantum Physics
Communication-Efficient Distributed Inverse Quantum Fourier Transform
F. Javier Cardama, Jorge Vázquez-Pérez, Tomás F. Pena et al. (+1 more)
The scalability of
quantum computing is currently limited by physical, technological, and architectural constraints that hinder the integration of a large number of
qubits within a single
quantum processor. Distributed
quantum computing (DQC) has therefore emerged as a viable alternative, aiming to interconnect multiple smaller
quantum processing units (QPUs) to jointly operate on a global
quantum state. While this paradigm enables scalable architectures, it introduces significant communication overhead due to the cost of non-local
quantum operations across distant nodes. In this work we propose a distributed formulation of the iQFT over a
quantum network composed of $P$ nodes, each hosting $Q$
qubits, enabling the execution on a logical register of size $n = P \cdot Q$. Furthermore, we introduce a communication-efficient variant based on a threshold-driven
pruning strategy, referred to as a communication horizon, which exploits the exponentially decreasing significance of controlled-phase rotations to safely omit remote gates with negligible impact. By reducing the number of inter-node
quantum interactions, the proposed approach significantly lowers the
quantum communication requirements of the distributed iQFT while preserving its functional correctness. Crucially, we show that this approach fundamentally alters the scaling of the
algorithm: the
entanglement resource consumption per node saturates to a constant value, reducing the global communication complexity from quadratic $\mathcal{O}(P^2)$ to linear $\mathcal{O}(P)$. As the iQFT constitutes a critical building block in many
quantum algorithms, the techniques presented in this paper directly contribute to improving the practicality and scalability of distributed
quantum computation.
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All authors F. Javier Cardama, Jorge Vázquez-Pérez, Tomás F. Pena, Andrés Gómez
Quantum Physics
Gate-Level Quantum Simulation of Nonunitary Linear Dynamics with Hybrid Oscillator-Qubit Architecture
Elin Ranjan Das, Muqing Zheng, Rishab Dutta et al. (+3 more)
We translate the one-mode
unitary-dilation framework for nonunitary linear dynamics into a gate-level hybrid oscillator–
qubit architecture. An ancillary oscillator encodes the kernel through state preparation and postselection, while a
qubit register simulates the discretized system operator. The construction applies to time-independent dynamics $\dot u=-(L+iH)u$, including discretized partial differential equations, and removes the $\mathcal{O}(\log M_a)$ ancilla-
qubit overhead of a discrete-variable (DV) $M_a$-term quadrature register. We bound the ideal state's squeezed-Fock coefficient-projection error, which decays superalgebraically in cutoff $N$ for Schwartz-class kernels and at a stretched-exponential rate under stronger joint decay and smoothness assumptions. The finite squeezed-Fock state generically has
stellar rank $N-1$, making $N$ a measure of the oracle's non-Gaussian resource. For oscillator dimension $N_{\mathrm{Fock}}$, a $p$th-order product formula reaches error $\epsilon_t$ in $\mathcal{O}(t^{1+1/p}N_{\mathrm{Fock}}^{(p+1)/(2p)}\epsilon_t^{-1/p})$ Trotter steps, up to generator-dependent commutator factors. A perturbation bound separates total scaled-map error from postselection probability. We
benchmark Law–Eberly synthesis and assess variational SNAP+$\mathcal D$ state preparation on heat and advection–
diffusion equations. At the prescribed DV sizing, the hybrid CV–DV route has smaller fixed-scale error in all ten instances, while the DV route accepts with fewer repetitions in every instance. These results quantify when a continuous qumode can replace a discretized ancilla register.
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All authors Elin Ranjan Das, Muqing Zheng, Rishab Dutta, Ang Li, Timothy Stavenger, Yuan Liu
Quantum Physics · Cross-listed from cond-mat.supr-con
Transverse Magnetic Response from Orbitally Polarized Cooper Pairs in Elemental Superconductors
Gabor Csire, Maria Teresa Mercaldo, Balazs Ujfalussy et al. (+2 more)
We demonstrate how crystalline
symmetry lowering, as for instance through strain, allows elemental
superconductors such as vanadium and niobium to realize
spin-singlet orbitally polarized Cooper pairs composed of electrons with identical orbital moments. Using superconducting density functional theory, we show that lowering of trigonal
symmetry to $C_s$, thus keeping only a single mirror plane, activates interorbital pairing in bulk and (111) surfaces, with a pronounced surface enhancement. In a
magnetic field, the resulting orbitally polarized superconducting state leads to a novel transverse
magnetic response. For in–plane field orientations that break the remaining mirror
symmetry, a sizable orbital magnetization emerges perpendicular to the applied field. We show that this effect is a direct consequence of equal–orbital-moment Cooper pairing, providing an experimentally accessible signature of this state. Our results establish strained elemental
superconductors as a minimal material platform for superconducting orbitronics.
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All authors Gabor Csire, Maria Teresa Mercaldo, Balazs Ujfalussy, Carmine Ortix, Mario Cuoco
Quantum Physics · Cross-listed from math-ph
Local topological order, Haag duality, and reflection positivity
Pieter Naaijkens, David Penneys and Daniel Wallick
In our previous article [arXiv:2307.12552], we introduced local topological order (LTO) axioms for abstract
quantum spin systems which allow one to access topological order via a boundary
algebra construction. Using the LTO axioms, we produced a canonical pure state on the quasi-local
algebra, which gives a net of von Neumann
algebras associated to a poset of cones in $\mathbb{R}^n$. In this article, motivated by [arXiv:2509.23734], we introduce an axiom for LTOs which ensures Haag duality for cone-like regions using Tomita-Takesaki theory. We prove this axiom is satisfied for all known topologically ordered commuting projector models. We thus get an independent proof of Haag duality for the Levin-Wen string net models originally proved in [arXiv:2509.23734]. We also give a reflection positivity axiom for LTOs, connecting to the recent article [arXiv:2510.20662]. We again prove this axiom is satisfied for all known topologically ordered commuting projector models about some $\mathbb{Z}/2$-reflection
symmetry.
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Quantum Physics · Cross-listed from cond-mat.supr-con
Ginzburg-Landau Theory for Confined Thin-Film Superconductors
Giovanni A. Ummarino and Alessio Zaccone
We develop a Ginzburg-Landau theory for superconducting thin films under
quantum confinement. Starting from the Ginzburg-Landau theory and the recently developed confinement theory of metallic thin films, explicit analytical expressions are derived for the coherence length, penetration depth, electronic mean free path, and Ginzburg-Landau parameter in confined geometries. The central result is that
quantum confinement directly renormalizes the intrinsic superconducting coherence length through confinement-induced modifications of the electronic density of states and
Fermi energy. This effect is absent in conventional thin-film transport theories based solely on surface scattering. As a consequence, confinement simultaneously suppresses the coherence length and enhances the penetration depth, thereby driving
superconductors toward stronger type-II behavior over a broad thickness range. The interplay between
quantum confinement and disorder can also produce reentrant type-I/type-II crossovers. The theory predicts a crossover regime in which confinement-induced renormalization of superconducting length scales and transport scattering become strongly intertwined. Comparison with recent penetration-depth measurements in Al thin films shows that the observed enhancement of the penetration depth originates from the interplay between confinement-induced renormalization of the coherence length and suppression of the effective mean free path by surface and disorder scattering. The results establish a direct connection between
quantum confinement and superconducting electrodynamics in confined metallic films.
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Quantum Physics
On the Simulation Cost of Quantum Finite Automata
Zeyu Chen and Junde Wu
This paper identifies exact probabilistic simulation cost as the natural quantitative measure of
quantum advantage for finite automata under strict cutpoints. It gives sharp simulation laws for two representative models. A one-way finite automaton with $c$ classical states and a $q$-dimensional
quantum register has exact probabilistic simulation cost $\Theta(cq^2)$, while an $n$-dimensional measure-once one-way
quantum finite automaton has worst-case cost $\Theta(n^2)$. The proofs develop a prepare–test framework, in which prefixes generate the relevant real operator degrees of freedom and suffixes convert them into strict-cutpoint tests. The same obstruction is recast through finite sign-rank
matrices, clarifying the role of Forster's spectral method. Placed beside the surrounding two-way separations, these results give a clean hierarchy of finite-automata
quantum advantage.
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Quantum Physics
Quantum Simulation of Magnetic Materials: from Ab-Initio to NISQ
Pascal Stadler, Florian G. Eich, Benedikt M. Schoenauer et al. (+5 more)
Quantum computers are increasingly accessible, yet demonstrations of physically meaningful simulations for real materials remain scarce. In our work we simulate low-energy
magnetic excitations, specifically
spin-wave spectra, of chromium tri-halide monolayers. Starting from ab-initio electronic structure calculations for these two-dimensional magnets, we derive an effective
spin model and simulate low-energy
spin excitations using a real-time propagation of the
spin system on the commercial
quantum computing cloud platform IQM Resonance. The results for systems with up to 48
qubits are validated against classical
benchmarks. While some spectral features remain challenging for today's NISQ devices, our simulation achieves good agreement at quasi-constant wall-time scaling, compared to the exponential scaling of classical methods. Our results demonstrate that, even in the absence of
quantum advantage, useful
quantum simulations of real materials are becoming possible for domain experts via commercial cloud access to
quantum computers.
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All authors Pascal Stadler, Florian G. Eich, Benedikt M. Schoenauer, Peter Schmitteckert, Michael Marthaler, Gary Schmiedinghoff, Peter K. Schuhmacher, Sebastian Zanker
Quantum Physics
Multivariate Decoded Quantum Interferometry for Weighted Optimization
Kaifeng Bu, Weichen Gu and Xiang Li
Decoded
Quantum Interferometry (DQI) is a recently introduced
quantum algorithm that reduces discrete optimization to decoding with potential advantages over the best-known
polynomial-time classical
algorithms for certain Max-LINSAT problems. In its original formulation, however, DQI treats all constraints uniformly and cannot exploit the weight structure present in most optimization problems of interest. In this work, we develop multivariate Decoded
Quantum Interferometry (multivariate DQI) for weighted optimization problems, focusing on the weighted Max-LINSAT problem over a
prime field. Grouping constraints into $N$ blocks by distinct weights, we introduce multivariate DQI states built from $N$-variable
polynomials of bounded total degree, and derive a closed-form asymptotic expression for both their optimal expectation value and their concentration behavior. We give an explicit preparation
circuit using a single decoder call, and extend the analysis to imperfect decoding. We also show that, for certain weighted OPI problems, multivariate DQI outperforms a natural weighted analogue of Prange's
algorithm, which serves as the weighted counterpart of the classical
benchmark used in the unweighted setting. Finally, we extend the ideas to
Hamiltonian DQI, obtaining approximate Gibbs states for commuting Pauli
Hamiltonians with block structure.
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Quantum Physics
Size-dependent dynamical instability of periodic $\mathcal{PT}$-symmetric scattering systems
Chao Zheng
While periodic $\mathcal{PT}$-symmetric structures offer a versatile platform for wave tailoring, their scattering responses are typically analyzed using stationary methods that presume dynamical stability. This assumption fails when time-growing bound states emerge, signaling a dynamical instability. Here, we analytically derive the instability threshold for a $\mathcal{PT}$-symmetric chain of $N$ unit
cells with gain/loss strength $\gamma$. Our $S$-
matrix analysis yields a closed-form threshold, $\gamma_c = 2\sin[\pi/(4N)]$, which scales as $\mathcal{O}(1/N)$ and vanishes in the thermodynamic limit. Consequently, enlarging such structures to access richer stationary band phenomena paradoxically triggers instability at weaker gain/loss. As confirmed by time-domain simulations, exceeding $\gamma_c$ causes exponentially growing bound states to overwhelm the system, rendering standard Bloch-wave descriptions physically irrelevant. Evaluated against this size-dependent threshold, many hallmarks of large $\mathcal{PT}$-symmetric structures, including gain-loss-induced localization, reflectionless transport, and coherent perfect absorbers and
lasers, are found to lie within the dynamically unstable regime. Our findings thus establish that physical transport in non-Hermitian periodic systems is governed by a fundamental interplay between stationary band theory and finite-size stability limits.
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Quantum Physics
Quantifying the Hadamard Resilience Effect and the Coherence Gap in NISQ-Era Classifiers
Wladimir Silva
We report on a fundamental disparity between
stochastic noise models and algorithmic performance in NISQ-era classifiers. Utilizing the ibm_kingston processor, we characterize the "Kingston Constant" ($\kappa \approx 0.07$), representing a 93% signal magnitude collapse. Despite this decay, we show via a hardware-calibrated
stochastic digital twin that a Hadamard Test based Perceptron maintains a 93.9% accuracy for the MNIST
dataset, validating our proposed Hadamard Resilience Effect under affine depolarization. Through parametric simulation, we establish a critical gate-noise threshold at $\lambda_{\text{crit}} \approx 0.65$ (corresponding to a critical signal retention $\alpha_{\text{crit}} \approx 0.35$) where topological rank preservation breaks down. Furthermore, physical execution at high feature depths ($N = 256$) reveals a systemic divergence—the “Coherence Gap” ($\Delta\rho \approx 0.91$)—where physical hardware classification accuracy collapses to 53.0% due to a “Coherence Wall” at a
circuit depth ($D \approx 10\text{k}$) exceeding the hardware's resilient depth limit ($D_{\text{max}} \approx 3.5\text{k}$). This gap is consistent with coherent phase errors and crosstalk being the dominant unmodeled contributors under the tested hardware configuration, establishing a predictive operational boundary for NISQ classification architectures.
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Quantum Physics
Distinct Signatures of Dynamical and Spectral Criticality in Quenched Quantum Batteries
Zheng Liu, Wen-Hui Nie, Yi-jia Yang et al. (+2 more)
Criticality is widely used to enhance energy storage in
quantum batteries. Two criticalities are compared here, one spectral and one dynamical. We ask two questions. Where does the enhancement that criticality brings to a quenched battery come from? And does the best charging performance require a critical point or a critical time? In the anisotropic XY chain, whose dynamics decomposes into independent momentum sectors, the weight each sector transfers to its upper level organizes the response. A closing spectral gap reshapes that weight near the closing momentum, so the stored energy responds sharply and controllably to the quench parameters. What it supplies is tunability rather than a larger maximum. A dynamical
quantum phase transition (DQPT) marks the time at which the evolving state becomes orthogonal to its initial state, where the stored energy stays smooth, and equals the energy maximum when the final precession frequencies coincide, as for a flat band away from the critical field. The interacting Ising chain has no momentum sectors, yet its energy maximum and its return peak separate by a tunable margin. Weak quenches reduce the stored energy to the static susceptibility of the quenched operator. These results identify what optimization acts on, the distribution of transition weights and the spread of precession frequencies, and turn the weak-quench response into a probe of the transition order.
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All authors Zheng Liu, Wen-Hui Nie, Yi-jia Yang, Lin-Cheng Wang, Chang-shui Yu
Quantum Physics
Quantum Hypergraph Partitioning
Cameron Ibrahim, Bao G. Bach, Jad Salem et al. (+4 more)
Quantum optimization
algorithms are inherently probabilistic, yet they are most often used to search for a single high-quality solution. In this paper, we instead study hypergraph partitioning problems in which the desired output is itself a probability distribution over partitions. We introduce a distributional perspective on hypergraph partitioning motivated by maximin and minimax objectives such as Fair Cut Cover, and we show how these objectives align naturally with the measurement distribution produced by QAOA. To motivate the formulation, we introduce a workforce-scheduling-inspired toy problem, the Greatest Expected Imbalance problem, in which the goal is to minimize the worst expected imbalance across hyperedges. We then develop QAOA-based
quantum solvers that represent distributional solutions natively through
quantum states, together with quadratic hypergraph objectives suitable for standard and multi-objective QAOA. These formulations connect balanced hypergraph partitioning, polarized community discovery, and distributional
fairness under a unified
quantum optimization framework. For comparison, we provide optimal
polynomial-time classical approximation
algorithms based on semidefinite programming and hyperplane rounding. Experiments on real-world and synthetic hypergraphs demonstrate that low-depth multi-angle QAOA can outperform these classical approximation baselines on the proposed objectives, highlighting the potential of
quantum algorithms for optimization problems where the solution is a distribution rather than a single partition.
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All authors Cameron Ibrahim, Bao G. Bach, Jad Salem, Reuben Tate, Kien X. Nguyen, Stephan Eidenbenz, Ilya Safro
Quantum Physics
Training continuously-coupled reconfigurable photonic chips with quantum machine learning
Denis Stanev, Nicolò Spagnolo and Fabio Sciarrino
Integrated photonic technologies have recently shown significant advances, enabling the possibility to implement reconfigurable interferometers with increasing size. One of the main tasks to fully exploit the capabilities of reconfigurable integrated interferometers is the possibility to precisely program their operation to perform a desired target
unitary. While recipes are known for
circuit layouts based on a cascade of beam-splitter and phase-shifter operations, a methodology applicable for reconfigurable continuously-coupled waveguide arrays is currently missing. Here, we devise a machine learning based approach for this task, using a black box methodology that does not rely on precise a-priori modeling of the
circuit internal architectures. We verify the effectiveness and the robustness of this approach via numerical simulations on different continuously-coupled waveguides layouts, either with planar or 3D structures. The proposed method makes use of a limited number of single- and two-
photon measurements, making it suitable for optical
quantum information processing. The obtained results open the perspective of employing this methodology as an effective tool to program the operation of integrated interferometers designed via different architectures.
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Quantum Physics · Cross-listed from physics.app-ph
Analytic Continuation Between Real- and Imaginary-Time Quantum Dynamics and the Fundamental Instability of Inverse Reconstruction
Pengfei Zhu
We develop a unified spectral-
semigroup framework that connects real-time and imaginary-time
quantum dynamics through analytic continuation. Within this formulation,
evolution is expressed as an exponential reweighting of spectral components generated by a single operator $\mathcal{G}$, placing
unitary and dissipative dynamics on equal footing within a common spectral structure. The mapping naturally induces a nonlocal fractional operator in time, giving rise to a contractive
semigroup governed by a square-root spectral deformation and identifying imaginary-time
evolution as an effective fractional low-pass filter. While exponential attenuation suppresses high-frequency components, the inverse transformation remains systematically controllable within a well-defined spectral window. In this regime, stable reconstruction of low-energy and coarse-grained dynamical features is achieved, establishing a predictive relation between imaginary-time
evolution and recoverable information. This leads to a quantitative description of a bandwidth-resolved asymmetry between forward propagation and inverse recovery. Across systems with continuous and discrete spectra, few-level coherence, and non-Hermitian generators, we demonstrate that spectral structure governs reconstruction fidelity in a unified manner. In particular, non-Hermitian and open-system settings reveal that irreversibility emerges as a geometry- and scale-dependent feature of the spectrum, tied to both damping and eigenstate non-orthogonality. These results recast analytic continuation as a structured, scale-dependent filtering process with quantifiable and systematically accessible reconstruction limits, providing a unified perspective on the interplay between dynamics, spectral geometry, and information recovery.
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Quantum Physics
Study of the Superradiance Phenomenon in the $\alpha$–attractor Potential using the Log Derivative Method
Ángel Salazar, Quray Potosí, David Laroze et al. (+3 more)
In this article, we solved the time–independent one–dimensional Klein–Gordon equation in the presence of $\alpha$–attractor potential using the Log derivative method. We calculated the reflection coefficient $\mathcal{R}$ and the transmission coefficient $\mathcal{T}$, showing that the superradiance phenomenon is present. In order to demonstrate the accuracy of our method, we performed a comparison with the analytical solution for the
hyperbolic tangent potential.
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All authors Ángel Salazar, Quray Potosí, David Laroze, Laura M. Pérez, Benjamín de Zayas, Clara Rojas
Quantum Physics
Perspective on tailoring quantum coherence with electron beams
Nahid Talebi
Examining and controlling the interaction between
semiconductor quantum qubits and their environment can boost
semiconductor quantum technologies, which have many applications in table-top
quantum computing hardware. Electron beams in electron microscopes have opened up a new avenue for the
quantum-coherent probing of
semiconductor excitations and strong-coupling effects. Here, I provide a brief overview of recent advancements in electron-beam probes for investigating
quantum coherence in
semiconductors and two-dimensional materials, complemented by my perspective on using electron beams to manipulate the
entanglement and correlations between
quantum systems.
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Quantum Physics
Cavity-Enhanced Collective Quantum Processing with Polarization-Encoded Qubits
Kamil Wereszczyński, Józef Cyran, Adam Brzezowski et al. (+4 more)
We introduce a cavity-enhanced optical architecture for collective
quantum processing in which logical
qubits are encoded in the polarization subspace of recirculating intracavity modes. The physical carrier and computational degree of freedom are explicitly separated: harmonic cavity bundles provide a stable resonant substrate, while programmable polarization transformations implement single-
qubit operations. A polarization-selective nonlinear interaction in the
entanglement region generates tunable controlled-phase gates, enabling a universal gate set. A parameter-scaling analysis shows that order-unity conditional phases are attainable in centimeter-scale cavities using experimentally accessible solid-state nonlinear media, without requiring extreme nonlinear coefficients, millisecond
photon lifetimes, or sub-hertz
laser stabilization. The results indicate that resonant recirculation provides a physically plausible platform for cavity based collective
quantum architectures.
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All authors Kamil Wereszczyński, Józef Cyran, Adam Brzezowski, Dawid Załużny, Robert Potoniec, Kasper Wiśniowski, Agnieszka Michalczuk
Quantum Physics · Cross-listed from cond-mat.quant-gas
Influence of pump size on pattern formation in exciton-polaritonic Bose-Einstein condensates in the non-Markovian regime
N. V. Kuznetsova, A. D. Alliluev, D. V. Makarov et al. (+1 more)
Dynamics of
exciton-polaritonic condensate under incoherent pumping is studied using the non-Markovian
stochastic Gross-Pitaevskii equation with the pseudo-differential dispersion term. This term corresponds to the lower energy branch of polaritons. It is shown that an increasing of the pumping spot area leads to the appearance of various spatial structures whose properties depend on the duration of the dynamical
memory. In the regime of short
memory time, condensate can form an extended state that spans outside the pumping area. We conclude that onset of such extended states is related to the specific form of the dispersion term causing the “traffic jam” effect. The case of long
memory time corresponds to enhanced condensate formation, when increasing of the pumping area leads to appearance of angular condensate structures which partially suppress emission of matter waves from the pumping area.
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All authors N. V. Kuznetsova, A. D. Alliluev, D. V. Makarov, A. A. Anisich
Quantum Physics
Quantum and classical processing with photonic quantum machine learning
J. C. López Carreño, S. Świerczewski, A. Opala et al. (+3 more)
Artificial intelligence and machine learning have been widely adopted both in the industry and in everyday life, but at the cost of high compute demands. Recent studies show that implementing machine learning in physical systems in the deep
quantum regime could not only lead to faster information processing, but also to perform tasks that are out of reach for classical systems. Here, we report a
quantum reservoir processing device capable of performing both
quantum and classical machine learning tasks. The implementation is realized with a programmable silicon chip excited with single
photons, a highly scalable and adaptable photonics technology. We successfully implement a variety of
quantum tasks, including
quantum state
tomography and measurement of
entanglement via negativity. Moreover, we implement a method of mitigation of experimental imperfections which results in a significant improvement in accuracy in comparison to the same system operating in the classical regime. Our results demonstrate a method to overcome a crucial bottleneck of
quantum technologies by providing a practical way of probing
quantum states.
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All authors J. C. López Carreño, S. Świerczewski, A. Opala, A. Salavrakos, B. Piętka, M. Matuszewski
Quantum Physics · Cross-listed from cond-mat.stat-mech
Renormalization of Quantum Operations: Parity-Time Transition and Chaotic Flows
Atsushi Oyaizu, Hongchao Li, Masaya Nakagawa et al. (+1 more)
The renormalization group (RG) in statistical physics focuses on ground-state properties of
equilibrium systems. However, it is unclear how it should be generalized to nonunitary
quantum dynamics caused by dissipation and measurement backaction, in which the notion of conserved energy is absent. Here, we extend the RG to cover nonunitary
quantum dynamics governed by
quantum operations. By performing coarse-graining in real time, we find that the competition between decoherence and coherent dynamics plays a decisive role in the behavior of the RG flow. In particular, we find that chaotic behavior without fixed points emerges in the RG flow when coherent dynamics is dominant, with the parity-time transition serving as a prototypical example. The measurement-induced parity-time transition belongs to the universality class of the one-dimensional Yang-Lee edge singularity, which serves as a guide for experimentally realizing imaginary fields in
lattice spin systems with a
quantum system.
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All authors Atsushi Oyaizu, Hongchao Li, Masaya Nakagawa, Masahito Ueda
Quantum Physics · Cross-listed from gr-qc
Quantum Correlations of Neutrinos in the Kerr-Newman Space-time
Ze-Wen Li and Shu-Jun Rong
Quantum phases establish a connection between gravitation and
quantum information, offering a novel avenue for exploring the properties of space-time. In this paper, we investigate the
quantum correlations (QCs) of
neutrinos in the Kerr–Newman space-time for both zero- and nonzero-angular-momentum propagation. The results show that, for zero-angular-momentum propagation, the oscillation periods of the survival probability and QCs progressively decrease with propagation distance in the inward direction. In the outward direction, increasing $M$ lengthens the oscillation periods of $P_{\nu_e\rightarrow\nu_e}$,
entanglement, and the monogamy of nonlocality, whereas increasing the angular momentum $a$ or charge $Q$ shortens them. For nonzero-angular-momentum propagation, the metric parameters also generate local profile modulations through additional two-path interference terms, rather than merely rescaling the oscillation period. Furthermore, we find that, despite differences in their ranges of variation,
entanglement and coherence exhibit highly consistent oscillatory behavior in both propagation cases. These findings provide a comprehensive understanding of
neutrino-based relativistic
quantum information.
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Quantum Physics
Operational time-reversal symmetry for unital qubit channels
Ouyang Ting, James Fullwood and Zhen Wu
The
Bayesian inverse of a
quantum channel $\mathcal{E}$ is a channel $\mathcal{F}$ in the reverse direction of $\mathcal{E}$ that yields time-symmetric correlations for sequential measurements performed on open
quantum systems. Such an operational form of time-reversal
symmetry for open
quantum systems is quite remarkable, as the dynamics of open
quantum systems are inherently irreversible due to system-environment interactions. Similar to the Petz map, a
Bayesian inverse $\mathcal{F}$ is defined with respect to a fiducial reference state $\rho$ for the channel $\mathcal{E}$. However,
Bayesian inverses do not always exist, and it is often a non-trivial task to determine the set of states $\rho$ for which a
Bayesian inverse of $\mathcal{E}$ exists. In this work, we solve the general problem of
quantum Bayesian inversion for unital channels acting on a single
qubit. Our analysis is streamlined by demonstrating that finding a
Bayesian inverse for a unital
qubit channel may be reduced to finding a
Bayesian inverse of a Pauli channel, which is simply a mixture of
unitary channels associated with the Pauli
matrices. As such, we provide a complete description of when operational time-reversal
symmetry is attainable for sequential measurements of a single
qubit in the presence of unital noise.
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Quantum Physics · Cross-listed from physics.optics
Partial Quantisation of Non-Hermitian Berry Phases in Time-Varying Media
Calvin Hooper
A fundamental
symmetry of the non-Hermitian operators describing wave-propagation in time-varying media imbue such systems with non-trivial
topology. This
topology may be measured directly in a wide range of experimental settings as a quantised real part of the Berry phase, contrasting unconstrained
geometric gain or loss. This topological index is provided explicitly for practical examples, including a non-Hermitian analogue of the Su-Schrieffer-Heeger model.
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Quantum Physics
SCALAR: A Neurosymbolic Framework for Automated Conjecture and Reasoning in Quantum Circuit Analysis
Sean Feeney, Pooja Rao, Andreas Klappenecker et al. (+5 more)
In this paper, we present SCALAR (Symbolic
Conjecture and LLM-Assisted
Reasoning), a neurosymbolic framework for automated
conjecture generation in
quantum circuit analysis built on top of the CUDA-Q open source framework. The system integrates
quantum simulation, symbolic
conjecture generation, and LLM-based interpretation. We evaluate SCALAR on 82 MaxCut instances from the MQLib
benchmark dataset and extend the analysis to 2,000 randomly generated graphs across four
topologies: regular, Erdos-Renyi, Barabasi-Albert, and Watts-Strogatz. The framework generates conjectured bounds relating optimal QAOA parameters to graph invariants, including known relationships such as periodicity constraints on the phase separation parameter $\gamma$. SCALAR also recovers previously reported parameter transfer phenomena across structurally similar instances. Additionally, the system identifies correlations between graph structural features and optimization landscape properties, which we characterize through invariant-based descriptors. Using CUDA-Q tensor network simulator, we scale experiments to instances of up to 77
qubits. We discuss the accuracy, generality, and limitations of the generated
conjectures, including sensitivity to graph class and
quantum circuit depth.
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All authors Sean Feeney, Pooja Rao, Andreas Klappenecker, Reuben Tate, Yuri Alexeev, Stefano Mensa, Elica Kyoseva, Stephan Eidenbenz
Quantum Physics · Cross-listed from physics.atom-ph
Amplitude Modulation Noise Suppression of Dynamic Atom Gravimeters
Wen-Zhang Wang, Jin-Ting Li, Dan-Fang Zhang et al. (+9 more)
Dynamic atom gravimeters enable absolute
gravity measurements on moving platforms. However, their performance is severely degraded due to the complex dynamic environment. This paper finds that the amplitude modulation noise (AMN) is a key factor contributing to the degradation of
gravity measurement performance. We find that the AMN is induced by the cold atomic cloud trajectory and velocity variation. We build a model to illustrate the principles and magnitude of AMN arising from various experiment processes. Then we propose a method to fit the normalized AMN respect to the kinematic parameters of the cold atomic cloud, and successfully suppress this noise from 0.11 to 0.038 using the fitting result. With this method, we improve the fringe phase resolution from 0.244 rad to 0.092 rad, and reduce the dynamic
gravity measurement noise from 2.69 mGal to 1.68 mGal. This study finds and suppresses a key noise source for the dynamic atom gravimeters, which is important for further improving its precision. The proposed method can be also applied for precision enhancement for other dynamic atom interferometer-based sensors, such as the atom gradiometers and gyroscopes.
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All authors Wen-Zhang Wang, Jin-Ting Li, Dan-Fang Zhang, Wei-Hao Xu, Jia-Yi Wei, Jia-Qi Zhong, Biao Tang, Lin Zhou, Run-Bing Li, Xi Chen, Jin-Wang, Ming-Sheng Zhan
Quantum Physics · Cross-listed from cond-mat.other
Beyond Topological Invariants: Order Parameters from Dominant Fock-state Patterns
Tsz Hin Hui, Xiaodan Xia, Pedro D. Sacramento et al. (+1 more)
We introduce a general scheme for constructing order parameters (OPs) by extracting generic patterns from the dominant Fock states of many-body ground states. While topological phases are traditionally characterized by non-local invariants, we demonstrate that our real-space OPs provide a more refined classification. In the extended Su-Schrieffer-Heeger model, we show that the standard winding number is insufficient to fully distinguish all phases; our OPs reveal a hidden sub-structure where each topological sector splits into two distinct phases. Beyond identifying the phase boundaries, these OPs quantify the depth of a phase, and remain robust in characterizing transitions in disordered systems. Furthermore, our approach provides a practical finite-size diagnostic for the Berezinskii-Kosterlitz-Thouless transition in the interacting
spin-1/2 XXZ model. The presented framework offers a broadly applicable tool for uncovering the phase diagrams of diverse interacting and non-interacting
quantum many-body systems.
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All authors Tsz Hin Hui, Xiaodan Xia, Pedro D. Sacramento, Wing Chi Yu
Quantum Physics
Giorgia Trotta, Paolo Scarafile, Paolo Facchi et al. (+5 more)
We investigate multipartite
entanglement via the statistical properties of pure
quantum states of n-
qubits. By analyzing the distribution of purity among balanced bipartitions, we compare Haar-typical states, uniformly distributed on the unit sphere of states, with Hadamard states, being characterized by equal weights in the computational basis. We analyze different ensembles of Hadamard states characterized by their phase distributions. Through analytical and numerical calculations, we show that Hadamard states exhibit, on average, a higher degree of
entanglement than Haar-typical states. In addition, we show that a particular class of Hadamard states, characterized by real coefficients with alternating signs, known as hypergraph states, appears especially relevant in the search for maximally multipartite entangled states, both for their structural simplicity and the increased likelihood of sampling highly entangled states. These results identify Hadamard states as a tractable yet promising class for exploring multipartite
entanglement structures and advancing the characterization of maximally multipartite entangled
quantum states.
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All authors Giorgia Trotta, Paolo Scarafile, Paolo Facchi, Giuseppe Magnifico, Angelo Mariano, Giorgio Parisi, Saverio Pascazio, Karol Życzkowski
Quantum Physics
Expander attention as exchange-correlation
Karim K. Alaa El-Din, Antonius v. Strachwitz and Sam M. Vinko
Kohn-Sham density functional theory (DFT) is the workhorse of
quantum chemistry, offering an attractive balance between accuracy and computational cost. Although exact in principle, DFT in practice relies on an approximation to the unknown exchange-correlation (XC) functional, which encodes the many-body
quantum effects beyond the mean-field treatment. Many such approximations exist, and machine-learned XC functionals have proliferated in recent years. A persistent challenge in this area is the trade-off between accuracy and computational cost: while high-accuracy ML functionals have shown success on strongly correlated systems that are notoriously difficult for conventional approximations, their unfavorable scaling has limited broader adoption. Here, we propose a linearly scaling non-local XC approximation based on an expander graph
transformer ansatz, improving the scaling of $O(N^2)$ or worse for previous ML functionals capable of reliably capturing strongly correlated systems. We show that it recovers the correct $\mathrm{H_2}$ dissociation curve in the strongly correlated regime, with promising results on planar $\mathrm{H_4}$, a system where even high-level coupled cluster methods break down. Our approach thus charts a path toward ML functionals that are both accurate on strongly correlated systems and cheap enough to deploy at scale.
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Quantum Physics
Parity Supervision as a Driver of Generalization in Quantum Generative Modeling
Markus Baumann, Daniel Hein, Steffen Udluft et al. (+3 more)
Generative models learn probability distributions in order to produce new samples beyond a finite training set. Their usefulness therefore depends on assigning probability to valid but previously unseen states. In a controlled
benchmark, we test whether parity-based training provides an inductive bias for this kind of generalization in instantaneous
quantum polynomial-time (IQP)
circuit Born machines. We compare the same IQP
circuit trained with parity supervision and coordinate-wise mean-squared error (MSE), together with classical controls. Parity supervision improves exact distributional fit and recovery of unseen high-value states over IQP-MSE. A
circuit-free spectral reconstruction shows that the matched parity moments already transfer evidence from observed samples to structurally compatible unseen states, while the IQP
circuit further refines this structure. These results identify parity supervision as both a tractable training signal and a generalization mechanism when the target distribution, training objective, and
circuit architecture are spectrally aligned.
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All authors Markus Baumann, Daniel Hein, Steffen Udluft, Tobias Rohe, Claudia Linnhoff-Popien, Jonas Stein