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Wednesday 15 July

Quantum Physics

Separating Geometry From Interference in Constrained Quantum Optimization

Chinonso Onah, Stuart Hadfield and Kristel Michielsen

We study the separation of geometric effects from quantum interference in quantum optimization algorithms. Constrained optimization problems such as routing, assignment, and scheduling are often encoded as product spaces of local variables, together with global feasibility penalties. The central algorithmic question we address is how a constraint-preserving mixing operator transports quantum amplitude across an exponential search space in the presence of local and global constraints. We develop a framework that separates three effects that are usually intermixed: amplitude transport, coherent interference among transported amplitudes, and problem-dependent classical postprocessing. We show that the mixing operator alone does not have a target-seeking ability. Concretely, the normalized distribution induced by its amplitude transport moves toward the distance profile of a uniformly random configuration. Thus, quantum sampling advantage may only arise when the phases of the many computational paths reaching a target configuration are sufficiently aligned for their amplitudes to reinforce. We show that, when the cost phases are engineered so that these paths add coherently, a number of circuit alternations growing only logarithmically with problem size suffices to convert the sum of their absolute contributions into a lower bound on the target amplitude, yielding a certified success probability independent of the ambient Hilbert-space dimension, the search-space size, or the feasible-set cardinality. We develop applications to problem-specific transpilation diagnostics, scalable hardware probes, constraint-induced classical maps of quantum-generated samples, the attribution of solution quality between the quantum distribution and classical post-processing in hybrid quantum-classical workflows and connections to distance-partitioned product spaces from classical coding theory.
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Quantum Physics

Filon Methods for Highly Oscillatory Controlled Quantum Systems

Spencer Lee and Daniel Appelö

Fast and accurate classical simulation of quantum systems is a central challenge in the design and control of quantum computers, but the highly oscillatory dynamics of these systems severely limit the efficiency of standard numerical methods. To address this, we adapt Filon quadrature for oscillatory integrals into two numerical methods, called Filon and Controlled Filon, for solving linear systems of ODEs with highly oscillatory solutions. We tailor both methods for efficient implementation in controlled quantum systems, and the Controlled Filon method additionally accounts for the oscillatory structure of the control pulses. We show by numerical experiments that these methods significantly reduce the computational cost of accurately simulating systems of superconducting transmon qubits by decreasing the number of timesteps needed to reach a given level of precision, with only a modest increase in the cost per timestep. For a realistic simulation of the dynamics of a CNOT gate, the Controlled Filon method is the most efficient method tested at every target accuracy, outperforming the best Hermite method by up to 6x and the Hermite method of the same order by up to 500x.
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Quantum Physics

Tensor Network decoding under inter-qubit correlated errors

Yue Yan, SiYing Wang, ZhiXin Xia et al. (+3 more)

The maximum likelihood decoder based on tensor networks has proven highly successful for the 2D surface code, achieving the optimal decoding success rate. However, existing tensor network decoders are typically designed for independent single-qubit error models, and their performance under inter-qubit correlated error models remains unexplored. This is due to two major challenges. The first challenge lies in constructing the tensor network for correlated errors, since the same final Pauli error can arise from many different combinations of independent and correlated errors, preventing a direct factorization of the error probability. The second challenge is that even after a tensor network is constructed, it generally contains huge-dimensional tensors and is therefore not efficiently contractible. In this work, to address the first difficulty, we introduce additional binary indices and two transformations to construct a multi-index tensor network for maximum-likelihood decoding with correlated errors. To address the second difficulty, we use reparametrization, elimination, and index classification to decompose the huge-dimensional tensors into lower-dimensional tensors. This yields an efficiently contractible tensor network for error models satisfying the tractability conditions derived in this work. We perform numerical simulations for a representative correlated error model and show that the maximum-likelihood decoder implemented with our multi-index tensor network construction achieves a higher finite-size threshold than the widely used MWPM decoder.
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All authors Yue Yan, SiYing Wang, ZhiXin Xia, HanNuo Yuan, CanWei Shi, Xiang-Bin Wang

Quantum Physics

Security Evaluation of Laser-Phase-Noise Quantum Random Number Generators with Intrinsic Correlations

Y. Gao, J.H Li, J.L. Liu et al. (+8 more)

Quantum random number generators are essential for achieving information-theoretical security in modern cryptographic systems. Among various implementations, laser phase noise schemes are widely favored for their simple architecture and high integration potential. However, the intrinsic correlations in the raw data are often neglected, which violates the independent and identically distributed assumption and potentially compromises system security. In this work, we establish an analytical model of correlation and formulate an analytical expression for the conditional min-entropy in the presence of intrinsic correlations to accurately quantify the genuinely extractable randomness. The validity of our theoretical model is confirmed by numerical simulations and experimental results, exhibiting excellent agreement. Under typical setups it is shown that neglecting intrinsic correlations leads to an overestimation of extractable randomness by approximately 46%. This work provides a valuable theoretical framework for designing compact, high-performance quantum random number generators with rigorous security analysis.
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All authors Y. Gao, J.H Li, J.L. Liu, M. Wu, L.J. Liu, H. Wang, Y. Pan, W. Huang, Y. Li, J. Yang, B.J. Xu

Quantum Physics

Basis-Independent Coherence Dynamics of Tripartite States under Pure Dephasing

Sovik Roy and Abhijit Mandal

Quantum coherence is a fundamental quantum resource whose preservation under environmental interactions is essential for quantum information processing. While most studies have focused on basis-dependent coherence measures, the dynamics of intrinsic coherence quantified by basis-independent measures remain largely unexplored. In this work, we investigate the dynamics of basis-independent quantum coherence for several representative tripartite pure and mixed states subjected to local and common dephasing environments in both Markovian and non-Markovian regimes. We show that Markovian local dephasing leads to state-dependent coherence degradation, whereas collective dephasing significantly enhances coherence preservation through decoherence-free sectors. More importantly, non-Markovian environments give rise to nearly frozen coherence dynamics for both pure and mixed states, demonstrating the remarkable robustness of intrinsic coherence against dephasing environment. A comparison with the measure of relative entropy of coherence reveals that basis-independent coherence measure exhibits substantially greater resilience and qualitatively different dynamical behaviour than its basis-dependent counterpart. These results provide new insights into the preservation of intrinsic multipartite coherence in open quantum systems and highlight basis-independent coherence as a robust quantum resource for realistic noisy quantum technologies.
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Quantum Physics

Quantum memory advantage for quantum process tomography

Carlos Bravo-Prieto, Weiyuan Gong and Antonio Anna Mele

Quantum process tomography, the task of learning an unknown quantum channel from black-box access, is a central problem in quantum information. In this setting, protocols with quantum memory can coherently store and jointly process quantum information obtained from multiple channel uses, whereas protocols without quantum memory must measure after each use and retain only a classical transcript of the measurement outcomes. A fundamental open question is whether quantum memory provides a query-complexity advantage even when protocols without quantum memory may adapt their experiments based on all previous outcomes with unbounded classical computational power. In this work, we show that it does. We determine the optimal query complexity of quantum process tomography without quantum memory up to a constant factor to be $\Theta(d_{\mathrm{in}}^3 d_{\mathrm{out}}^3/\varepsilon^2)$, where $d_{\mathrm{in}}$ and $d_{\mathrm{out}}$ are the channel input and output dimensions, respectively, and $\varepsilon$ is the target diamond-norm accuracy. More precisely, we prove that any incoherent protocol for this task, including adaptive protocols, requires $\Omega(d_{\mathrm{in}}^3 d_{\mathrm{out}}^3/\varepsilon^2)$ queries, even when each channel use may be assisted by arbitrary fresh ancilla, and we present a non-adaptive, ancilla-free incoherent protocol achieving the matching upper bound $O(d_{\mathrm{in}}^3 d_{\mathrm{out}}^3/\varepsilon^2)$. Our results thereby generalize the optimal sample-complexity bounds for single-copy state tomography, recovered as the special case $d_{\mathrm{in}}=1$. By contrast, coherent protocols with quantum memory achieve query complexity $\Theta(d_{\mathrm{in}}^2 d_{\mathrm{out}}^2/\varepsilon^2)$. Hence, our results establish a rigorous learning separation between quantum process tomography with and without quantum memory.
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Quantum Physics · Cross-listed from cs.LG

PQFA: Parallel Quantum Feature Augmentation of Fused Representations for Multimodal Classification

Mingzhu Wang and Yun Shang

Most multimodal learning methods improve how heterogeneous representations are aligned and fused, while post-fusion enhancement remains less explored. We propose Parallel Quantum Feature Augmentation (PQFA), a hybrid quantum-classical framework that applies multiple shallow variational quantum circuits to fused multimodal features. Text and image representations extracted by frozen RoBERTa and ViT encoders are processed through bidirectional cross-attention, attentive pooling, and adaptive gated fusion. The fused feature is then amplitude-encoded into parallel quantum circuits, whose measurement readouts are concatenated with the classical representation for prediction. We evaluate PQFA on MM-IMDb and N24News through controlled comparisons using the same encoders, fusion backbone, data splits, projection dimension, and augmentation output width. PQFA consistently outperforms both the fusion backbone without quantum augmentation and a width-matched MLP augmentation baseline, while using approximately 2.2K augmentation parameters compared with 24.0K for the MLP branch. Missing-modality experiments further show improved robustness when textual or visual inputs are incomplete, with particularly clear gains when the more informative textual modality is severely degraded. Controlled ablations and feature-space analyses indicate that the improvement cannot be reproduced by random feature mappings, increased classical width, or untrained quantum transformations. Quantum-state diagnostics additionally show stable predictive performance across the tested simulated noise levels and distinct branch-specific transformations of the encoded states. These results establish PQFA as an effective and parameter-efficient strategy for post-fusion augmentation in hybrid quantum-classical multimodal learning.
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Quantum Physics

Security evaluation of quantum distance-bounding protocols via semidefinite programming

Kevin Bogner, Aysajan Abidin, Dave Singelee et al. (+1 more)

Quantum distance-bounding (QDB) protocols let a verifier check that a prover is both genuine and physically nearby. During a timed fast phase of quantum communication, the verifier measures round-trip times to obtain an upper bound on the prover's distance. For a uniform comparison, we isolate the fast phase and study one-round distance-fraud (DF) and mafia-fraud (MF) games. For discrete-variable QDB, we show that these games reduce to convex optimization problems and can therefore be solved exactly with semidefinite programming; each MF value comes with an explicit attack achieving it and a matching certificate that no attack does better. This contrasts with quantum position verification, where an attack is split between two separated parties, so its optimization is nonconvex and analyses rely on relaxations. In our MF game, the cooperating pair collapses to a single sequential strategy, which keeps the game convex and its exact value computable. Across the discrete-variable protocols we examine, the best one-round DF attack succeeds with the same probability ($1/2$) for every protocol, whereas MF clearly separates the protocols. For continuous-variable QDB, we report estimated attack success probabilities from a calibrated Gaussian attack model. The benchmark covers protocols whose fast phase itself authenticates the prover; designs that follow Brands and Chaum and instead bind the fast phase with a final authenticated message, like the earliest QDB proposal, fall outside it and are treated separately. Of the four protocols studied, two had no previously known one-round attack values, and we report the first ones; for the other two, we find MF attacks with higher success probability than previously reported. Overall, one-round MF resistance depends on whether an attacker can use information revealed early by the prover to answer a fresh challenge from the verifier.
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All authors Kevin Bogner, Aysajan Abidin, Dave Singelee, Bart Preneel

Quantum Physics

Deterministic single-electron trapping on solid neon using engineered dielectric surface geometry

Kundan Surse, Eric Helgemo, Andrew Palmer et al. (+5 more)

Levitating electron qubit on the surface of solid neon has recently emerged as a promising and intrinsically noise-resilient platform for quantum information processing. Their ultra-clean, inert environment suppresses conventional decoherence pathways associated with lattice disorder, charge traps, and nuclear-spin baths that limit coherence in semiconductor qubits. Yet, uncontrolled surface features such as bumps, valleys, and electrode-defined gaps can bind electrons unintentionally, contributing charge noise and inducing spin-orbit coupling mediated decoherence. To address this challenge, we propose an engineered interface in which a dielectric layer is deposited beneath the solid neon to provide an atomically smooth template, eliminating surface-roughness induced trapping. By selectively etching this dielectric layer at desired qubit locations, deterministic potential minima can be engineered to reliably capture electrons while suppressing unwanted surface bound states. We perform large-scale Schrodinger and Poisson simulation to compare the existing and proposed strategies of electron trapping on neon, obtaining good agreement with recent experimental measurements.
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All authors Kundan Surse, Eric Helgemo, Andrew Palmer, Md Serajum Monir, Lukas Delventhal, Thanh Nguyen, Maja Cassidy, Rajib Rahman

Quantum Physics

Suppressing Detuning-Induced Bias in Ramsey Magnetometry with Composite Pulses

Shingo Kukita, Kento Nawata and Yuichiro Matsuzaki

Quantum sensing estimates a physical parameter encoded in the state of a probe; with independent spin probes the precision follows the standard quantum limit. Studies of sensing precision often assume that the parameters entering the model, such as the noise, are known. In practice these parameters are not always known, and a mismatch between the assumed and actual values induces a systematic error. Here we study single-qubit Ramsey magnetometry of a DC magnetic field under an unknown detuning between the actual and nominal spin frequencies: A first pulse puts the qubit into a superposition of its two states, the field to be sensed then adds a relative phase during an exposure stage, and a second pulse enables the readout. In our setting, the field acts only during the exposure stage, whereas the detuning acts throughout the whole protocol. We analyze how the detuning biases the estimate, preventing the total estimation error from following the standard quantum limit. We then construct a composite-pulse preparation and readout that exploits the difference in the intervals over which the field and the detuning act to cancel the detuning to first order. We evaluate the performance of this composite-pulse protocol and show that it suppresses the detuning-induced bias.
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Quantum Physics

Deterministic Quantum Phase Estimation with Linear Circuit Complexity in a Photonic System

M. Midhuna, Ajay Jayachandran, Kanad Sengupta et al. (+2 more)

Quantum algorithms solve certain computational problems faster than the best known classical algorithms. Many algorithms, including Shor's for factoring, Grover's for unstructured search, and the HHL for solving linear systems, rely on quantum phase estimation (QPE) as a fundamental subroutine. The QPE protocol proceeds through the initialization of a control register in a uniform superposition, controlled unitary evolution encoding the eigenphase, and a final inverse quantum Fourier transform followed by measurement to extract the phase. Here, we address a special class of unitary operators that frequently appear in quantum Fourier transform-based protocols, cyclic group representations, and periodically evolving quantum systems. We introduce a QPE algorithm that successfully reduces the circuit complexity from $\mathcal{O}(n^2)$ to $\mathcal{O}(n)$ for a special class of unitary operators and implement it on a four-qubit photonic system. The four-qubit system is realised using a photon pair, with two qubits encoded in its polarization degree of freedom and the remaining two in its path modes. In contrast to previous photonic implementations of QPE based on dual-rail encoding and KLM protocol, where controlled operations are inherently probabilistic and thus reduce the overall success probability of phase estimation, our scheme is fully deterministic. Moreover, it is scalable to higher-dimensional unitaries, provided the underlying structure of the unitaries is preserved.
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All authors M. Midhuna, Ajay Jayachandran, Kanad Sengupta, Akshai T. Krishnan, C. M. Chandrashekar

Quantum Physics

A Physics-Grounded QUBO Encoding of Irrigation Scheduling for QAOA

Alisher Ortikov and Alisher Ilhamov

Rotational irrigation scheduling in water-scarce Central Asia is a densely coupled combinatorial problem: soil-moisture memory links each irrigation decision to all later days within a zone, field adjacency couples zones on overlapping window days, and rigid canal rotations quantize water delivery in time. We formulate it as a Quadratic Unconstrained Binary Optimization (QUBO) by linearizing the root-zone water balance, so the quadratic crop-stress objective generates the physical couplings as 2-local Ising interactions with no higher-order terms; only the water-budget constraint requires an artificial all-to-all penalty, which we certify with an instance-adaptive weight bound an order of magnitude tighter than generic prescriptions. Every instance is built from observed data for a cotton district in Khorezm, Uzbekistan: NASA POWER meteorology, FAO-56 Penman–Monteith evapotranspiration, SoilGrids~2.0 hydraulics, measured capillary fluxes, and documented canal-rotation windows that enter as qubit-count reductions. We benchmark four tiers – exact solvers, matched-budget heuristics, ideal-statevector quantum approximate optimization algorithm (QAOA), and noise-model plus IBM Heron execution – and add a scaling study on soil instances up to 584 variables. Exact branch-and-bound proves optimality in seconds through 150 variables, and heuristic degradation at fixed evaluation budget is repaired by scaling the budget, so no classical scalability wall appears at deployment-relevant sizes, and none is claimed. On hardware, the informative signal is optimum-sampling enrichment over uniform sampling. We claim no quantum advantage; we deliver a physically grounded, data-complete, reproducible encoding of a societally critical scheduling problem for the quantum-utility era.
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Quantum Physics

Quantum annealing in SU(3) multiplet space with nonlocal drivers

Yang Wei Koh

A theoretical framework for quantum annealing based on $\mathfrak{su}(3)$ algebra is proposed, and applied to the problem of overcoming first-order transitions in rugged energy landscapes. Conservation of the Casimir invariant means that one can work with irreducible representations of $\mathfrak{su}(3)$, avoiding the exponentially large Hilbert spaces of spin glass systems. In this framework, quantum drivers exhibit nonlocal properties in the sense that during annealing the wave function can be transported far away from a local minimum, thereby avoiding being trapped by it. We consider Hamiltonians with two quantum drivers and studied them numerically. It is shown that energy gap closures can be circumvented via a suitable path in the parameter space of the two drivers. Comparison with more traditional annealing driven by transverse field and antiferromagnetic operators suggests that $\mathfrak{su}(3)$ drivers are more effective in attaining the global minimum of rugged energy landscapes.
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Quantum Physics · Cross-listed from cs.PF

HybridQC: Hardware-Grounded Simulation of Tightly Integrated Hybrid Quantum-Classical Systems

Panayiotis Christou, Shuwen Kan and Ying Mao

Hybrid quantum-classical performance depends on how quantum processors share classical compute, controllers, memory, and communication links. Circuit simulators and provider measurements expose kernel and job behavior, but leave topology-level questions about controller bottlenecks, quantum capacity, and mixed-workload contention unanswered. We present HybridQC, a discrete-event simulator for configurable hybrid compute units (HCUs). Users specify resource graphs containing classical compute, memory, controllers, quantum annealing (QA) and digital quantum computing (DQC) devices, and links. Jobs become dependent stages for preparation, quantum execution, transfers, reconstruction, and postprocessing. Finite capacities and selectable scheduling policies determine where stages wait and overlap. Service profiles use measurements from D-Wave Advantage 1 and Advantage 2 and IBM Kingston, Marrakesh, and Fez, separating physical quantum-processor occupancy from cloud wall time. Mean absolute percentage errors are 3.92%-8.04% for D-Wave access time and 5.26%-19.01% for IBM quantum seconds. Balanced 10x HCU scaling improves makespan by 2.19x-3.42x, while policy choice changes makespan by 1.80x for a mixed workload with 20 jobs per workload family. Scaling depends on which inputs grow: 100x data growth yields median runtime near 306 s, while 100x joint growth in circuits, shots, and depth reaches 4.806 x 10^7 s on the fixed HCU. HybridQC enables designers to study topology, scheduling, and workload growth before tightly integrated quantum-classical machines exist physically.
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Quantum Physics

TandemQEC: Joint Provisioning of Streaming Quantum Error Correction in Tightly-Integrated Quantum-Classical Systems

Panayiotis Christou, Shuwen Kan, Rongda Kang et al. (+2 more)

Fault-tolerant quantum applications require timely classical decoding and feedback. Component benchmarks leave open how contention across processors, links, and finite buffers affects application progress. We propose TandemQEC, a system-level simulator connecting applications, code-specific quantum error correction schedules, and physical modalities. It models dependencies, resource availability, and buffer occupancy to explain joint provisioning decisions. We validate TandemQEC using analytical and CUDA-Q Logical references and measured pipelines. Across 960 repeated GPU/CPU runs using CUDA-Q Realtime, median absolute relative errors are 1.06% for median latency and 1.74% for 95th-percentile latency. Separate CPU-window validation covers PyMatching and BP-OSD across five code families. Studies span superconducting, trapped-ion, and neutral-atom modalities. At 32 concurrent jobs, increasing decoder capacity and bandwidth by 8x together achieves a 4.17x speedup, while either upgrade alone reduces runtime by at most 2.1%. 4x faster syndrome extraction even raises runtime under fixedduration protection due to generating more classical work. Joint upgrades recover reference performance. These findings show why component improvements require balanced provisioning to benefit applications. TandemQEC identifies useful resource combinations before complete systems are available.
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All authors Panayiotis Christou, Shuwen Kan, Rongda Kang, Hao Wang, Ying Mao

Quantum Physics

A versatile laser-machined rf trap for arrays of 100+ ions

Frank G. Schroer, Ilyoung Jung, Thomas W. Burkle et al. (+4 more)

Large ion crystals in diverse geometries are a key resource for quantum simulation experiments. In this work, we introduce a macroscopic rf trap that supports a wide variety of one-dimensional ion configurations as well as lateral two-dimensional crystals with more than 100 ions. Our design is based on precision-machined fused silica wafers that are stacked to form the trap structure. Ten independently biased electrodes provide flexible control over the axial potential, enabling long one-dimensional crystals, isospaced ion strings, split-well chains, and two-dimensional arrays with tunable aspect ratios. We present the design and fabrication process for this trap and demonstrate the ability to tune the radial secular frequencies, detect and compensate micromotion, rotate the principal axes, and characterize trapped ion heating rates. All trap design and documentation files are freely available alongside this work, to facilitate adoption and further development within the ion trap community.
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All authors Frank G. Schroer, Ilyoung Jung, Thomas W. Burkle, Jack B. Lyons, Joseph W. Van Vlack, Joseph Ezuma, Philip Richerme

Tuesday 14 July

Quantum Physics · Cross-listed from cond-mat.stat-mech

Gaussian Reformulation of the Feynman Path Integral for Quantum Statistical Mechanics with Results for the Second Virial Coefficient of $^4$He

Phil Attard

The Feynman path integral for quantum statistical mechanics is reformulated as Gaussian sampling of the neighborhood of each position configuration. The variance and mean are obtained from ring polymer statistics on a lattice, and from the high temperature expansion of the Wigner-Kirkwood commutation function, respectively. The algorithm avoids multiple temperature nodes for each configuration and the need for numerical cancelation in the statistical averages, which are problematic for conventional path integral quantum Monte Carlo. Analytic and simulation results for the second virial coefficient of helium are compared to laboratory measurements.
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Quantum Physics · Cross-listed from math.NA

Tensor Network Methods for Advection-Diffusion-Reaction Systems Using Quantum-Inspired Representations

Nahid Binandeh Dehaghani, Rafal Wisniewski and A. Pedro Aguiar

We present a quantum-inspired tensor-network framework for solving advection-diffusion-reaction (ADR) partial differential equations. Discretized solution fields are encoded as matrix product states (MPS), while differential operators are represented as matrix product operators (MPOs). Time integration is performed entirely in tensor-network form using explicit Euler updates with controlled truncation. The method is evaluated on one- and two-dimensional ADR problems and compared with high-accuracy Runge-Kutta reference solutions. Numerical results show that the proposed representation remains compact, stable, and accurate across a range of dynamical regimes. The solver captures both local solution profiles and global observables while maintaining small bond dimensions throughout the simulation. These results highlight the potential of tensor networks as efficient structure-preserving tools for PDE simulation in multiple spatial dimensions.
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Quantum Physics · Cross-listed from cs.AR

A Reality Check on Quantum Optimisation: Evidence from an Industrial Case Study

Hila Safi, Karen Wintersperger, Oliver von Sicard et al. (+2 more)

Quantum Processing Units promise speed-ups for selected computational problems, including combinatorial optimisation, but their industrial utility remains an open challenge. We study an industrial variant of the Job-Shop Scheduling Problem using quantum, quantum-inspired, and classical methods across three platforms: IBM Quantum, the D-Wave Quantum Annealer, and the Fujitsu Digital Annealer. By tailoring formulations to hardware-specific constraints, we show that hardware-software co-design is essential for solution quality and scalability. We benchmark all approaches against an exact classical solver and a MILP formulation, evaluating runtime, solution quality, and scalability. Our results indicate that quantum and quantum-inspired optimisation can support industrial solver selection, integration in classical workflows, modelling decisions, and early proof-of-concept development, while suggesting a potential path towards improved approximations for industrial scheduling.
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All authors Hila Safi, Karen Wintersperger, Oliver von Sicard, Christoph Niedermeier, Wolfgang Mauerer

Quantum Physics

Precision quantum simulation of magnon spectra and interactions

Trond I. Andersen, Nikita Astrakhantsev, Jeronimo Martinez et al. (+329 more)

Quantum simulation promises to advance materials discovery by accurately simulating complex states of matter, their microscopic excitations, and macroscopic response functions. The central challenge in resolving the underlying interacting dynamics is to combine high-fidelity evolution with the sophisticated control necessary to manipulate individual quasi-particles in quantum many-body states. Here, we report on high-precision simulation of both linear and non-linear response functions in a 2D XY spin-1/2 magnet using an analog-digital superconducting processor of up to 97 qubits. By interleaving digital gates with analog evolution precisely characterized via Hamiltonian learning, we selectively excite magnons at tunable energy densities. Measuring first the linear magnon response – a central probe in neutron-scattering experiments – we extract temperature-dependent spectra and lifetimes. Our results reveal stark variations in magnon decay rates across the Brillouin zone, with enhancement near van Hove singularities and suppression for edge-localized modes. Next, we perform a suite of nonlinear measurements, including the study of self-scattering mechanisms, as well as pump-probe spectroscopy to directly characterize the magnon interactions. While matrix-product state simulations capture the dynamics well in either small systems or at low temperatures, their predictions become inaccurate away from these limits. This work demonstrates precise simulation of the interacting dynamics in quantum magnets, and provides key insights into quasi-particles and their microscopic scattering mechanisms.
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All authors Trond I. Andersen, Nikita Astrakhantsev, Jeronimo Martinez, Will Morong, Johannes Motruk, Dario Rossi, Brayden Ware, Bryce Kobrin, Weijie Wu, Elizabeth Bennewitz, Manuel Rudolph, Tom Westerhout, Amira Abbas, Rajeev Acharya, Laleh Aghababaie Beni, Ross Alcaraz, Sayra Alcaraz, Markus Ansmann, Frank Arute, Kunal Arya, Walt Askew, Juan Atalaya, Christopher Ayala, Ryan Babbush, Brian Ballard, Joseph Bardin, Hector Bates, Andreas Bengtsson, Majid Bigdeli Karimi, Alexander Bilmes, Simon Bilodeau, Felix Borjans, Alexandre Bourassa, Jenna Bovaird, Dylan Bowers, Leon Brill, Peter Brooks, Michael Broughton, David Browne, Brett Buchea, Bob Buckley, Tim Burger, Brian Burkett, Jamal Busnaina, Nicholas Bushnell, Jonas Bylander, Anthony Cabrera, Juan Campero, Hung-Shen Chang, Silas Chen, Zijun Chen, Ben Chiaro, Liang-Ying Chih, Agnetta Cleland, Bryan Cochrane, Matt Cockrell, Josh Cogan, Paul Conner, Tom Connolly, Harold Cook, Rodrigo Cortinas, William Courtney, Alexander Crook, Benjamin Curtin, Adam Dally, Sayan Das, Martin Damyanov, Dripto Debroy, Himadri Dey, Stijn de Graaf, Laura De Lorenzo, Sean Demura, Lucia De Rose, Agustin Di Paolo, Leon Ding, Howard Dobbs, Paul Donohoe, Ebru Dogan, Ilya Drozdov, Andrew Dunsworth, Rasmus Edholm, Valerie Ehimhen, Alec Eickbusch, Aviv Elbag, Lior Ella, Mahmoud Elzouka, David Enriquez, Catherine Erickson, Lara Faoro, Vinicius Ferreira, Marcos Flores, Leslie Flores Burgos, Sam Fontes, Ebrahim Forati, Jeremiah Ford, Brooks Foxen, Masaya Fukami, Alan Fung, Lenny Fuste, Suhas Ganjam, Gonzalo Garcia, Christopher Garrick, Robert Gasca, Helge Gehring, Robert Geiger, Élie Genois, William Giang, Dar Gilboa, James Goeders, Edward Gonzales, Raja Gosula, Alejandro Grajales Dau, Dietrich Graumann, Joel Grebel, Alex Greene, Jonathan Gross, Jose Guerrero, Tan Ha., Steve Habegger, Tanner Hadick, Ali Hadjikhani, Michael Hamilton, Monica Hansen, Matthew Harrigan, Sean Harrington, Jeanne Hartshorn, Stephen Heslin, Paula Heu, Oscar Higgott, Reno Hiltermann, Jeremy Hilton, Hsin-Yuan Huang, Michael Hucka, Christopher Hudspeth, Ashley Huff, William Huggins, Aditya Jayaraman, Evan Jeffrey, Shaun Jevons, Zhang Jiang, Xiaoxuan Jin, Cody Jones, Chaitali Joshi, Kelsey Josund, Pavol Juhas, Andreas Kabel, Bharath Kannan, Hui Kang, Kiseo Kang, Amir Karamlou, Ryan Kaufman, Tanuj Khattar, Mostafa Khezri, Seon Kim, Paul Klimov, Can Knaut, Alexander Korotkov, Fedor Kostritsa, John Mark Kreikebaum, Ryuho Kudo, Arun Kumar, Ben Kueffler, Vladislav Kurilovich, Vitali Kutsko, Nathan Lacroix, Tiano Lange-Dei, Brandon Langley, Pavel Laptev, Kim-Ming Lau, Emma Leavell, Loïck Le Guevel, Justin Ledford, Joy Lee, Kenny Lee, Brian Lester, Wendy Leung, Matthew Lloyd, Lily Li, Wing Li, Ming Li, Alexander Lill, Mike Lindmark, William Livingston, Aditya Locharla, Erik Lucero, Daniel Lundahl, Aaron Lunt, Sid Madhuk, Donald Macaskill, Aniket Maiti, Ashley Maloney, Salvatore Mandra, Leigh Martin, Orion Martin, Eric Mascot, Paul Masih Das, Anselme Massimino, Melvin Mathews, Cameron Maxfield, Jarrod McClean, Matthew McEwen, Seneca Meeks, Anthony Megrant, Tim Menke, Kevin Miao, Zlatko Minev, Reza Molavi, Sebastian Molina, Shirin Montazeri, Akira Nakamura, Charles Neill, Konstantin Nesterov, Michael Newman, Roselle Ngaloy, Anthony Nguyen, Murray Nguyen, Chia-Hung Ni, Murphy Niu, Nicholas Noll, Sergey Novikov, Logan Oas, Ricky Oliver, Will Oliver, Raymond Orosco, Kristoffer Ottosson, Alice Pagano, Manan Patel, Sherman Peek, David Peterson, Alex Pizzuto, Thomas Plumb-Reyes, Elias Portoles, Rebecca Potter, Orion Pritchard, Sam Probst, Michael Qian, Chris Quintana, Matthew Rakher, Arpit Ranadive, Ganesh Ramachandran, Armin Razavi, Matthew Reagor, Rachel Resnick, David Rhodes, Daniel Riley, Gabrielle Roberts, Roberto Rodriguez, Emma Ropes, Eliott Rosenberg, Emma Rosenfeld, Dario Rosenstock, Elizabeth Rossi, Pedram Roushan, David Rower, Robert Salazar, Kannan Sankaragomathi, Murat Sarihan, Kevin Satzinger, Max Schaefer, Sebastian Schroeder, Henry Schurkus, Aria Shahingohar, Michael Shearn, Aaron Shorter, Shvarts Vladimir, Vlad Sivak, Spencer Small, W. Clarke Smith, David Sobel, Barrett Spells, Sofia Springer, George Sterling, Scott Stonemeyer, John Su, Jordan Suchard, Youngkyu Sung, Aaron Szasz, Alex Sztein, Tomoyuki Tanaka, Madeline Taylor, Jothi Thiruraman, Douglas Thor, Brandur Thorgrimsson, Dogan Timucin, Eifu Tomita, Alfredo Torres, M. Mert Torunbalci, Hao Tran, Abeer Vaishnav, Justin Vargas, Gopinath Vasalamarri, Sergey Vdovichev, Guifre Vidal, Benjamin Villalonga, Meghan Voorhees, Steven Waltman, Jonathan Waltz, Shannon Wang, Danni Wang, James Watson, Yonghua Wei, Travis Weidel, Theodore White, Kristi Wong, Bryan Woo, Christopher Wood, Maddy Woodson, Cheng Xing, Z. Jamie Yao, Ping Yeh, Bicheng Ying, Juhwan Yoo, Noureldin Yosri, Elliot Young, Grayson Young, Adam Zalcman, Ran Zhang, Yaxing Zhang, Yiqing Zhou, Ningfeng Zhu, Nicholas Zobrist, Zhenjie Zou, Sergio Boixo, Yu Chen, Julian Kelly, Hartmut Neven, Vadim Smelyanskiy, Dvir Kafri, L. B. Ioffe, Kostyantyn Kechedzhi, Xiao Mi, Dmitry Abanin

Quantum Physics

A Measurement Plane for Quantum Networking

Abderrahim Amlou, Amar Abane, Anouar Rahmouni et al. (+6 more)

Quantum networking testbeds lack a distinct plane for coordinating distributed measurements and collecting experimental data across heterogeneous devices. To address this gap, we present the Measurement Plane, a dedicated plane that complements the data, control, and management planes rather than replacing or extending their pipelines. The contribution is presented as a distributed framework that organizes measurement functions into four layers: application, experiment coordination, capability, and resource agents. Our design separates user workflows from device-specific control. We implemented the framework as containerized microservices connected through publish–subscribe messaging, and validated it on a two-node quantum networking setup connected by an optical network. The framework successfully coordinated remote nodes to execute coincidence measurement and polarization entanglement distribution experiments with visibility interference of up to 98 percent. This evaluation demonstrated the effectiveness of the framework for supporting complex, distributed quantum experiments, enabling online measurement and feedback, and significantly reducing manual configuration and execution effort.
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All authors Abderrahim Amlou, Amar Abane, Anouar Rahmouni, Mheni Merzouki, Abdella Battou, Ahmed Lbath, Ya-Shian Li-Baboud, Oliver Slattery, Thomas Gerrits

Quantum Physics · Cross-listed from physics.optics

Exactly Solvable Diffraction-Grating Scattering Problems for TE and TM waves

Farhang Loran and Ali Mostafazadeh

In J.~Phys.~A 31, 3493 (1998), Berry provides an analytic solution of the problem of determining the diffracted beam intensities for atoms incident upon a grating given by the potential, $v(x,y):=iV_0(e^{i\mathfrak{K}\,y}-1)$ for $0\leq x\leq\ell$ and $v(x,y):=0$ otherwise, where $V_0, \mathfrak{K}$, and $\ell$ are positive real parameters. This result, which relies on the paraxial approximation, readily applies to the diffraction of transverse electric (TE) waves by the nonmagnetic optical grating given by the relative permittivity, $\hat\varepsilon(x,y):=1-v(x,y)/k^2$, where $k$ is the incident wavenumber. We show that Berry's grating belongs to a larger class of possibly magnetic diffraction gratings whose scattering problem for both TE and transverse magnetic (TM) waves are exactly solvable. Our analysis makes use of a recently developed dynamical formulation of stationary scattering that is based on the idea of mapping the scattering problem to the quantum dynamics generated by an effective non-Hermitian Hamiltonian operator. {We use this formulation to derive explicit analytic expressions for the diffracted beam amplitudes that are valid beyond paraxial approximation.} As a concrete example, we offer the exact solution of the scattering problem for TE and TM waves incident upon a generalization of Berry's grating.
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Quantum Physics

Quantum Motion from Local Transition Susceptibility

Jan Klaers

We characterize quantum motion through the susceptibility of a quantum state to weak localized state conversion. The susceptibility can be related to a passage speed characterizing local motion independently of probability transport. For individual WKB branches, it reproduces the magnitude of the local dispersion velocity in both propagating and evanescent regions. In the relativistic theory, the inferred passage speed is bounded by the speed of light, reaching this bound at the finite energy corresponding to the center of the mass gap, where the evanescent decay length equals the reduced Compton wavelength. This identifies the reduced Compton wavelength as the shortest stationary
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Quantum Physics

Let the Qudit Do the Jacobi: A Structured Quantum Algorithm for Spectral Decomposition

A. Mandilara

Jacobi diagonalization is a long-established numerical algorithm for the spectral decomposition of Hermitian and, more generally, normal matrices. In this work, we develop a qudit-native quantum realization of the Jacobi diagonalization algorithm for unknown unitary operators. The proposed framework avoids explicit reconstruction of the operator and controlled-unitary operations. Each elementary two-parameter Givens rotation is implemented through two sequential single-parameter quantum variational optimizations that are directly accessible experimentally. An interferometric protocol is further introduced for extracting the eigenvalues of the diagonalized unitary, up to an overall global phase. Numerical simulations on ensembles of Haar-random unitary matrices demonstrate that the proposed algorithm preserves the characteristic convergence behavior of the classical Jacobi method and exhibits the expected quadratic scaling in the number of elementary operations with the dimension $d$, comparable to its classical counterpart. The results establish the proposed algorithm as a structured quantum numerical linear algebra algorithm naturally suited to qudit architectures and provide a bridge between classical iterative matrix algorithms and their quantum realizations.
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Quantum Physics

Comparing the three W-like states with the W state

Dafa Li

In [Phy. Rev. Lett., 98, 260501 (2007)] and previous papers, the W-like states were used in many quantum communication schemes, distillation, teleportation and superdense coding. So far, no one has compared the W-like states with the W state. We investigate the properties of three W-like states named as $|\vartheta ^{\prime }\rangle $, $|\eta ^{\prime }\rangle $ and $|\xi ^{\prime }\rangle $. We point out that $|\vartheta ^{\prime }\rangle $ (resp. $|\eta ^{\prime }\rangle $ and $|\xi ^{\prime }\rangle $) has the maximal von Neumann entanglement entropy (vNEE) $S(\rho _{A})=\ln 2$ (resp. $S(\rho _{B})=\ln 2$ and $S(\rho _{C})=\ln 2$) and the maximal tangle $\tau _{A(BC)}=1$ (resp. $\tau _{B(AC)}=1$ and $\tau _{C(AB)}=1$) while the W state does not. We also indicate that if some one of three qubits is traced out, then the remaining two qubits of $|\vartheta ^{\prime }\rangle $ (resp. $|\eta ^{\prime }\rangle $ and $|\xi ^{\prime }\rangle $) are more entangled than the two qubits of the W state by several entanglement measures. It means that the three W-like states have higher robustness against some particle loss than the W state. We show that $|\vartheta ^{\prime }\rangle $, $|\eta ^{\prime }\rangle $ and $|\xi ^{\prime }\rangle $ can be suitable for perfect teleportation and superdense coding but the W state cannot.
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Quantum Physics

A Fibre-Integrated SPDC Heralded Single-Photon Source Using Zn-Indiffused PPLN Ridge Waveguides at Telecom Wavelengths

Peter Iveson, Paolo L. Mennea, Goronwy Tawy et al. (+7 more)

We report a fibre-integrated heralded single-photon source based on a commercial Zn-indiffused MgO:PPLN ridge waveguide operated in Type-0 degenerate spontaneous parametric down-conversion (SPDC). The device emits a broadband spectrum spanning approximately 70 nm across the telecom C-and L-bands, with an absolute brightness of $9.1\times 10^{9}$ pairs/(s mW). After accounting for optical losses, we determine an internal heralding efficiency of 58(5)%. The source maintains high purity, exhibiting a coincidences-to-accidentals ratio exceeding $9\times 10^{4}$ and a heralded second-order correlation of $g_{\text{h}}^{(2)}(0) = (5.53 \pm 0.46)\times 10^{-4}$. Low multi-photon noise and broadband emission demonstrate the viability of such platforms for wavelength-multiplexed quantum networking.
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All authors Peter Iveson, Paolo L. Mennea, Goronwy Tawy, Rex H. S. Bannerman, Noe Palomar-Davidson, Lewis D. Wright, Patrick M. Ledingham, Peter G. R. Smith, James C. Gates, Corin B. E. Gawith

Quantum Physics

An Information-Theoretic Characterization of Optimal Value-Readout in Response-Register Quantum Oracles

Milad Ghadimi, Hesam Soltanpanahi and Vahid Salari

Response-register quantum oracles admit two complementary operational interpretations: value readout and phase kickback. Although their computational equivalence is well understood, the quantitative relation between these two operational interpretations has lacked an exact characterization. We prove that, for finite Abelian response groups, the optimal single-query value-readout probability is exactly the normalized Rényi-1/2 effective Fourier support of the response state. This identity provides an exact information-theoretic characterization of optimal value-readout capability, gives the Rényi-1/2 effective Fourier support a direct operational interpretation in the oracle setting, and yields a tight phase–value complementarity theorem together with an explicit family of saturating response states.
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Quantum Physics

Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth

Giacomo Antonioli, Anna Bernasconi, Alessandro Berti et al. (+2 more)

Matrix chain multiplication – computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$ – arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present Two-Tower Matrix Multiplication, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.
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All authors Giacomo Antonioli, Anna Bernasconi, Alessandro Berti, Gianna M. Del Corso, Alessandro Poggiali

Quantum Physics

Robust Nonperturbative Trapped-Ion Quantum Logic

Luca Stefanescu and Florian Mintert

Entangling gates of trapped ions are typically mediated by collective motional degrees of freedom. Weak coupling between qubit and motional degrees of freedom and the resulting harmonic dynamics give access to a broad range of gate schemes, but also impose strict limitations on achievable gate times. In this paper, we devise optimally designed driving schemes for the realization of fast, high-fidelity entangling gates mediated by anharmonic dynamics. The driving can also be optimized to achieve resilience to multiple system imperfections, and the anharmonicity in the motional dynamics can be used to enhance such resilience.
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Quantum Physics

Emulating XX catalysts for quantum annealing via self-consistent transverse fields

Mohammadhossein Dadgar and Christopher L. Baldwin

Fully-connected transverse interactions have been considered as catalysts for quantum annealing that could mitigate exponentially small gaps and circumvent first-order phase transitions, but their experimental implementation remains challenging. In this work, we introduce a procedure for emulating their effects via a self-consistent transverse field. All that is required beyond conventional transverse-field annealing is the ability to make measurements in the transverse ($\hat{\sigma}^x$) basis. We show that this protocol yields identical dynamics in the large-system limit, and study the approach to that limit in numerical simulations of the (uniform) $p$-spin model. However, realizing the protocol in practice requires us to consider a series of approximate variants, each of whose errors we quantify and demonstrate can be made sufficiently small. Lastly, we show how to map the protocol onto annealing platforms that vary only a single control parameter. Even after the multiple stages of approximation, our procedure can generate dynamics that agree well with the original transverse-interaction catalyst, establishing self-consistent transverse fields as a viable alternative on near-term quantum annealers.
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