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Physics Quantum Physics

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Monday 16 March

Quantum Physics

A Deep-Learning-Boosted Framework for Quantum Sensing with Nitrogen-Vacancy Centers in Diamond

Changyu Yao, Haochen Shen, Zhongyuan Liu et al. (+13 more)

Nitrogen-vacancy (NV) centers in diamond are a versatile quantum sensing platform for high sensitivity measurements of magnetic fields, temperature and strain with nanoscale spatial resolution. A common bottleneck is the analysis of optically detected magnetic resonance (ODMR) spectra, where target quantities are encoded in resonance features. Conventional nonlinear fitting is often computationally expensive, sensitive to initialization, and prone to failure at low signal-to-noise ratio (SNR). Here we introduce a robust, efficient machine learning (ML) framework for real-time ODMR analysis based on a one-dimensional convolutional neural network (1D-CNN). The model performs direct parameter inference without initial guesses or iterative optimization, and is naturally parallelizable on graphics processing units (GPU) for high-throughput processing. We validate the approach on both synthetic and experimental datasets, showing improved throughput, accuracy and robustness than standard nonlinear fitting, with the largest gains in the low-SNR regime. We further validate our methods in two representative sensing applications: diagnosing intracellular temperature changes using nanodiamond probes and widefield magnetic imaging of superconducting vortices in a high-temperature superconductor. This deep-learning inference framework enables fast and reliable extraction of physical parameters from complex ODMR data and provides a scalable route to real-time quantum sensing and imaging.
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All authors Changyu Yao, Haochen Shen, Zhongyuan Liu, Ruotian Gong, Md Shakil Bin Kashem, Stella Varnum, Liangyu Li, Hangyue Li, Yue Yu, Yizhou Wang, Xiaoshui Lin, Jonathan Brestoff, Chenyang Lu, Shankar Mukherji, Chuanwei Zhang, Chong Zu

Quantum Physics

Learning Quantum Operator Dynamics from Short-Time Data

Jinyang Li, Satoshi Iso, Shunji Matsuura et al. (+2 more)

Real-time dynamics of quantum observables provide direct access to excitation spectra and correlation functions in quantum many-body systems, but currently available quantum devices are limited to short evolution times due to decoherence. We propose a neural ordinary differential equation (Neural ODE) framework with a physics-driven neural network to reconstruct long-time operator dynamics from short-time quantum data. By expanding observables in the Pauli basis and exploiting locality and symmetry constraints, the operator evolution is reduced to a tractable set of coefficients whose dynamics are learned from the measurement data. Applied to the Ising spin chain with mixed fields, the operator learning method accurately extrapolates its long-time correlation function and resolves its excitation spectrum. We validate the framework by collecting short-time data from IBM's superconducting quantum processor and successfully reconstruct the Fourier spectrum of an $N=8$ Ising spin chain with 5 times enhanced precision. Our results demonstrate a scalable and data-efficient strategy for extracting dynamical and spectral information from practical quantum hardware.
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All authors Jinyang Li, Satoshi Iso, Shunji Matsuura, Lingxiao Wang, Xiaoyang Wang

Quantum Physics

Adaptive Control of Stochastic Error Accumulation in Fault-Tolerant Quantum Computation

Tirtha Haque

In realistic hardware for quantum computation that possesses fault-tolerance, non-stationary noise and stochastic drift lead to logical failure from the temporal accumulation of errors, not from independent events. Static decoding and fixed calibration techniques are structurally incompatible with this situation because they do not take into account temporal correlations between errors or control-induced back-action of errors. These effects motivate control policies that must track noise evolution across correction cycles, rather than respond to individual syndromes in isolation. We treat fault-tolerant quantum computation as a stochastic control problem, modelled using reduced quantum dynamics in which Pauli error processes are governed by latent noise parameters that vary temporally. From this perspective, logical failure arises through the accumulation of a hazard variable, and the corresponding control objective depends on the full history of observations. Operating under these conditions, a Chronological Deep Q-Network (Ch-DQN) maintains an internal belief state that tracks both noise evolution and accumulated hazard. During training, backward refinement of trajectories is used to sample slowly drifting modes of operation, while runtime inference remains strictly causal. A fractional meta-update stabilizes learning in the presence of non-stationary, control-coupled dynamics. Through multi-distance simulations that incorporate stochastic drift and feedback from decision-making, Ch-DQN suppresses hazard accumulation and extends logical survival time relative to static and recurrent baselines. Error correction in this regime is therefore no longer a static decoding task, but a control process whose success is determined over time by the underlying noise dynamics.
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Quantum Physics · Cross-listed from physics.chem-ph

Stochastic Collision Theory of Magnetism in Radical Fluids

Yoshiaki Uchida and Ryohei Kishi

How stochastic, microscopic events generate deterministic, macroscopic properties is a fundamental question in physics. We address this question by developing a quantum master equation model for concentrated radical solutions, where random molecular collisions govern the magnetic properties of the system. Our theory reveals a simple mechanism: the first-order exchange contribution averages to zero over collisions, while the second-order term survives as an effective ferromagnetic coupling that enhances magnetization. The model captures the experimentally observed trends in magnetic behavior that deviate from conventional theories. Because the mechanism arises from statistical averaging, it may apply to a broader class of soft matter phenomena, including liquid crystals.
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Sunday 15 March

Quantum Physics

Computing logical error thresholds with the Pauli Frame Sparse Representation

Thomas Tuloup and Thomas Ayral

We introduce a sparse classical representation, a truncation strategy and a shot-efficient sampling method to push the classical prediction of quantum error correction thresholds beyond Clifford operations and Pauli errors. As two illustrations of the potential of our method, we first show that coherent noise error thresholds, when computed at the circuit level (i.e taking into account full syndrome circuits) for distances up to d=9, are systematically overestimated (by a factor of about 4) by a Pauli-twirling approximation of the noise. We then apply our method to the recently introduced magic-state cultivation protocol. We show, through shot-efficient importance sampling, that, at distance d=5, the multiplicative factor between the T-gate and the S-gate injection error rate is not the one conjectured from low-d computations: it can be as large as 7.
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Quantum Physics

Exact characterizations for quantum conditional mutual information and some other entropies

Zhou Gang

Lieb and Ruskai's strong subadditivity theorem, which shows that the conditional mutual information must be nonnegative, is fundamental in quantum theory. It has numerous applications, such as in quantum error correction. When the mutual information is zero, the Petz recovery map can be used to reconstruct the quantum channel. When the mutual information is small, one seeks to define an optimal recovery channel. To this end, a mathematical characterization of the mutual information is desirable. We address this problem by providing an exact characterization of the mutual information, along with characterizations for other entropies. Our controls are sharp, leaving no room for improvement, in the sense that we provide equalities, regardless of whether the mutual information (or remainder) is small or large. We transform the definitions of these entropies into a summation of explicitly constructed terms, and the definition of each term obviously demonstrates the desired positivity/convexity/concavity. The summation converges rapidly and absolutely in a chosen elementary norm.
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Quantum Physics

GPU-Accelerated Quantum Simulation of Stabilizer Circuits

Muhammad Osama, Dimitrios Thanos and Alfons Laarman

We introduce new parallel algorithms for efficiently simulating stabilizer (Clifford) circuits on GPUs, with a focus on data-parallel tableau evolution and scalable handling of projective measurements. Our approach reformulates key bottlenecks in stabilizer simulation – such as Gaussian elimination and measurement updates – into GPU-tailored primitives that eliminate sequential dependencies and maximize memory coalescing. We implement these techniques in QuaSARQ, a GPU-accelerated stabilizer simulator designed for large qubit counts and many-shot sampling. Across a broad benchmark suite reaching 180,000 qubits and depth 1,000 (roughly 130M gates), QuaSARQ shows substantial runtime improvements, with up to 105$\times$ speedup, and over 80% energy reduction on demanding instances. Moreover, QuaSARQ consistently outperforms Stim, a state-of-the-art CPU-optimized stabilizer simulator, as well as Qiskit-Aer (CPU/GPU), Qibo, Cirq, and PennyLane. Finally, QuaSARQ exhibits a significant advantage in many-shot sampling on large workloads. These results demonstrate that our parallel algorithms can significantly advance the scalability of stabilizer-circuit simulation, particularly for workloads involving extensive measurements and sampling.
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Quantum Physics

Evaluating Calibration-Based Digital Twins for IBM Quantum Hardware Simulation

Edgars Bautra, Maksims Dimitrijevs and Abuzer Yakaryilmaz

We evaluate calibration-based digital twins for IBM Quantum hardware, aiming to reproduce hardware measurement outcomes on classical simulators. We present a workflow that builds twins from downloadable calibration CSV files by mapping coherence times, gate and readout error rates, and operation durations to thermal-relaxation, depolarizing, and readout error channels, while reconstructing a directed coupling map to restore connectivity constraints during transpilation. We compare four twin variants (CSV-built, backend-derived simulator, backend-derived noise model, and fake-backend snapshots) under a common execution and validation protocol. Experiments on two IBM QPUs, ibm_brisbane and ibm_sherbrooke, use randomized five-qubit circuits of depths 10, 20, and 30 across four optimization levels. Weighted Jaccard similarity indicates that twins constructed from downloadable calibration CSV data often achieved the closest agreement with hardware, while backend-derived twins provided competitive and practical baselines. The results further show that agreement depends on both the target device and the transpilation settings, underscoring the need to validate digital twins for the specific execution setup rather than assuming transferability across devices.
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Quantum Physics

IQP Born Machines under Data-dependent and Agnostic Initialization Strategies

Sacha Lerch, Joseph Bowles, Ricard Puig et al. (+3 more)

Quantum circuit Born machines based on instantaneous quantum polynomial-time (IQP) circuits are natural candidates for quantum generative modeling, both because of their probabilistic structure and because IQP sampling is provably classically hard in certain regimes. Recent proposals focus on training IQP-QCBMs using Maximum Mean Discrepancy (MMD) losses built from low-body Pauli-$Z$ correlators, but the effect of initialization on the resulting optimization landscape remains poorly understood. In this work, we address this by first proving that the MMD loss landscape suffers from barren plateaus for random full-angle-range initializations of IQP circuits. We then establish lower bounds on the loss variance for identity and an unbiased data-agnostic initialization. We then additionally consider a data-dependent initialization that is better aligned with the target distribution and, under suitable assumptions, yields provable gradients and generally converges quicker to a good minimum (as indicated by our training of circuits with 150 qubits on genomic data). Finally, as a by-product, the developed variance lower bound framework is applicable to a general class of non-linear losses, offering a broader toolset for analyzing warm-starts in quantum machine learning.
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All authors Sacha Lerch, Joseph Bowles, Ricard Puig, Erik Armengol, Zoë Holmes, Supanut Thanasilp

Quantum Physics · Cross-listed from cond-mat.str-el

Microwave spin resonance in epitaxial thin films of spin liquid candidate TbInO3

Sandesh S. Kalantre, Johanna Nordlander, Margaret A. Anderson et al. (+2 more)

Minimizing the energy of a many body system tends to favor order, but classical frustration and quantum fluctuations destabilize that order. The tension between these effects can produce exotic quantum states of matter. Quantum spin liquid (QSL) states emerge in models of localized magnetic moments where the crystal lattice connectivity frustrates ordering, and the exchange interaction of neighboring spins strengthens quantum fluctuations. Experimentally identifying a QSL in a real material is challenging from the lack of an order parameter. Piecing together evidence from varied techniques is necessary for diagnosing the nature of the ground state – QSL or otherwise – of a frustrated spin system. In this work, we use coplanar superconducting resonators to probe magnetic excitations in epitaxially grown thin films of a spin liquid candidate TbInO3. Adapting microwave techniques from the field of circuit quantum electrodynamics, we measure responses of these thin films whose volume is too low for applying conventional bulk techniques. In-plane susceptibility extracted from the spin resonance signal indicates extreme frustration of magnetic order down to 20 mK, over two orders of magnitude lower than the Curie-Weiss energy scale. Through a crystal field analysis, we identify the doublet eigenstates comprising the ground state. As a consequence of improper ferroelectricity, Tb moments split into two flavors with distinct g-factors reflecting the local crystal field environment of each site. Spin-orbit coupling, crystal fields, magnetic frustration and improper ferroelectricity distinctively combine to shape the magnetic ground state of TbInO3. This work establishes a measurement technique using superconducting resonators to probe thin films of frustrated magnets, and applies this technique towards building a coherent understanding of the magnetic properties of TbInO3.
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All authors Sandesh S. Kalantre, Johanna Nordlander, Margaret A. Anderson, Julia A. Mundy, David Goldhaber-Gordon

Quantum Physics

Reversible Lifetime Semantics for Quantum Programs

Simone Faro, Francesco Pio Marino and Gabriele Messina

Reversible computation requires that intermediate data be explicitly undone rather than discarded. In quantum programming, this principle appears as uncomputation, usually treated as a technical cleanup mechanism. We instead present uncomputation as a semantic foundation. In the Qutes language, we introduce a formal model of Scope-Bounded Liveness-Guided Uncomputation, where lexical scope bounds variable lifetime and static liveness and entanglement analysis determine the earliest safe reclamation point. We define semantic lifetime and a Restoration Invariant ensuring that temporary quantum information disappears once it becomes semantically irrelevant. We prove compositional correctness under nested scopes and show that early reclamation can reduce circuit depth by avoiding critical-path overhead and can bound peak live qubits through disciplined ancilla reuse. Finally, we show that parameter passing semantics emerges from the same lifetime discipline, with pass-by-value and pass-by-reference corresponding to different lifetime boundaries, and we characterize the constraints (irreversibility, persistent entanglement, and aliasing) under which automatic uncomputation must be restricted.
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Quantum Physics

Parrondo-type enhancement of quantum-state transfer in spin chains

Rafael Vieira and Edgard P. M. Amorim

Spin chains have been widely studied as quantum channels for short-distance communication in quantum devices, where many-body dynamics can mediate quantum-state transfer between distant sites. In finite unmodulated chains, however, dispersion and interference effects associated with the static Hamiltonian often limit the achievable transfer fidelity. Here we investigate the transfer of single-qubit and Bell states in finite $XX$ spin chains under periodic switching between two Hamiltonians with different boundary couplings. Inspired by Parrondo's paradox, we examine whether alternating between two configurations that individually yield suboptimal transfer fidelities can generate enhanced coherent transmission. Using Floquet theory together with numerical simulations in the single-excitation subspace, we show that periodic driving can outperform static configurations and achieve higher transfer fidelities. This enhancement originates from the noncommutativity of the driven Hamiltonians and reflects a purely coherent interference effect. We further analyze the dependence of the protocol on system size and driving parameters and examine its robustness to asymmetric boundary couplings. Our results show that the transfer fidelity remains stable under moderate disorder, indicating that simple time-dependent control of boundary couplings provides an effective strategy to enhance quantum-state transfer in spin-chain communication channels and optimize quantum information processing in engineered many-body systems.
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Quantum Physics · Cross-listed from cond-mat.str-el

Variance reduction for forces and pressure in variational Monte Carlo

David Linteau, Saverio Moroni, Giuseppe Carleo et al. (+1 more)

We present simple and practical strategies to reduce the variance of Monte Carlo estimators. Our focus is on variational Monte Carlo calculations of atomic forces and pressure in electronic systems, although we show that the underlying ideas apply more broadly to other observables, like pair-correlation and angular-distribution functions, and other methods, including molecular dynamics. For Pulay-type contributions, we show that a minor modification based on the Metropolis acceptance ratio softens the power-law divergence of the variance to a logarithmic one, and that inexpensive regularizations can further suppress outliers at the price of a controlled small bias. For Hellmann-Feynman forces, we derive compact variance-reduced estimators for periodic systems that are straightforward to implement in standard Monte Carlo codes. The approach is illustrated for high-pressure metallic hydrogen with more than a hundred atoms described by neural quantum states, including an application to molecular dynamics driven by the improved forces.
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All authors David Linteau, Saverio Moroni, Giuseppe Carleo, Markus Holzmann

Quantum Physics · Cross-listed from cs.LG

Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State

Nicholas Gao, Till Grutschus, Frank Noé et al. (+1 more)

Neural-network wave functions in Variational Monte Carlo (VMC) have achieved great success in accurately representing both ground and excited states. However, achieving sufficient numerical accuracy in state overlaps requires increasing the number of Monte Carlo samples, and consequently the computational cost, with the number of states. We present a nearly constant sample-size approach, Multi-State Importance Sampling (MSIS), that leverages samples from all states to estimate pairwise overlap. To efficiently evaluate all states for all samples, we introduce Excited Pfaffians. Inspired by Hartree-Fock, this architecture represents many states within a single neural network. Excited Pfaffians also serve as generalized wave functions, allowing a single model to represent multi-state potential energy surfaces. On the carbon dimer, we match the $O(N_s^4)$-scaling natural excited states while training $>200\times$ faster and modeling 50% more states. Our favorable scaling enables us to be the first to use neural networks to find all distinct energy levels of the beryllium atom. Finally, we demonstrate that a single wave function can represent excited states across various molecules.
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All authors Nicholas Gao, Till Grutschus, Frank Noé, Stephan Günnemann

Quantum Physics

Quantum Enhanced Pauli Propagation

S. Majumder, J.R. Garrison, L. Luo et al. (+8 more)

Accurately estimating observables on noisy quantum devices remains a central challenge for near-term quantum algorithms. While quantum error mitigation techniques can reduce noise-induced bias, they often rely on unverifiable assumptions about the circuit noise, and cannot guarantee the magnitude of residual bias error. Here, rather than using classical resources to mitigate a noisy quantum circuit execution, we propose a hybrid algorithm that uses quantum resources to improve the accuracy of approximate classical Pauli-path simulation. Our protocol, Quantum Enhanced Pauli Propagation (QuEPP), uses Clifford perturbation theory (CPT) to construct a classically simulable ensemble of Clifford circuits from the low-order terms in CPT, which directly provide the approximate classical Pauli-path simulation of the target circuit. Noisy quantum expectation values of this ensemble are then used to infer a global rescaling factor that corrects quantum execution of the target circuit, providing higher-order contributions absent from the truncated low-order classical simulation. This approach requires no noise characterization, applies to arbitrary circuits, and provides a provable route to asymptotically unbiased estimates. Using IBM Heron hardware, we demonstrate QuEPP on 2D random mirror circuits of up to 49 qubits and circuit depth 80, as well as Trotterized Hamiltonian evolution, showing consistent improvements beyond classical CPT and unmitigated quantum results. QuEPP offers a simple, scalable, and model-free framework for enabling accurate quantum computation in the pre-fault-tolerant era.
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All authors S. Majumder, J.R. Garrison, L. Luo, B. Mitchell, M. Amico, A. Seif, M. Tran, K. Sharma, E. van den Berg, Z. Minev, L. C. G. Govia

Quantum Physics

The Twin-World road to reality in quantum mechanics

Daniel Braun

I introduce a novel realistic, stochastic approach to quantum mechanics by extending the recently proposed grabit formalism \cite{braun_stochastic_2022} to two Twin Worlds. According to the picture developed, we live at the intersection of two worlds with identical stochastic laws of evolution. Our World is limited to that intersection, and only coincidence events from the two Twin Worlds, post-selected automatically by our restriction to the intersection, have physical reality in Our World. This fully reproduces standard non-relativistic quantum mechanics, including Born's rule and the violation of Bell's inequality. I derive the stochastic evolution equation in each Twin World that fully reproduces Schrödinger's equation for an arbitrary number of particles with arbitrary interactions, and demonstrate that hall-mark quantum effects such as tunnling are correctly reproduced.
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Quantum Physics

Quantum-limited traveling-wave parametric amplifier based on DUV-defined planar structures

Hao Li, Marco Scigliuzzo, Evgenii Guzovskii et al. (+3 more)

The relentless scaling of classical microelectronics has been enabled by the precision and reproducibility of deep-ultraviolet (DUV) optical lithography. Implementing large-scale superconducting quantum processors will require cryogenic microwave components that follow a similarly scalable fabrication path. This need is particularly acute for high circuit-density devices such as traveling-wave parametric amplifiers (TWPAs), where recent implementations have demonstrated high gain, broad bandwidth, high saturation power, and near-quantum-limited noise, but trade-offs between footprint, insertion loss, and scalable integration remain. Here, we demonstrate a four-wave-mixing TWPA fabricated via a hybrid scheme that combines DUV-defined planar circuit elements with electron-beam-patterned Josephson junctions, constituting a first step toward fully scalable manufacturing. The device combines a compact footprint of 6.6 mm $\times$ 6.6 mm with broadband gain over the measured 3-11 GHz span and an average 1 dB compression point of -102 dBm. By using planar capacitors to reduce loss, it operates near the quantum limit, with an average added noise of 0.4 photons above the standard quantum limit in the 4 to 8 GHz band. The phase-matching stopband remains narrow, with a bandwidth of 43 MHz, consistent with resonator-frequency variation below 1% and indicative of the circuit-parameter uniformity enabled by DUV lithography. These results show that DUV-defined planar elements can enable compact, low-loss, near-quantum-limited TWPAs and provide a promising route toward high-density cryogenic microwave hardware for large-scale quantum systems.
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All authors Hao Li, Marco Scigliuzzo, Evgenii Guzovskii, Seog-Tae Han, Kyungho Han, Tobias J. Kippenberg

Quantum Physics

How to find expressible and trainable parameterized quantum circuits?

Peter Röseler, Dennis Willsch and Kristel Michielsen

Whether parameterized quantum circuits (PQCs) can be systematically constructed to be both trainable and expressive remains an open question. Highly expressive PQCs often exhibit barren plateaus, while several trainable alternatives admit efficient classical simulation. We address this question by deriving a finite-sample, dimension-independent concentration bound for estimating the variance of a PQC cost function, yielding explicit trainability guarantees. Across commonly used ansätze, we observe an anticorrelation between trainability and expressibility, consistent with theoretical insights. Building on this observation, we propose a property-based ansatz-search framework for identifying circuits that combine trainability and expressibility. We demonstrate its practical viability on a real quantum computer and apply it to variational quantum algorithms. We identify quantum neural network ansätze with improved effective dimension using over $6 \times$ fewer parameters, and for VQE on $\mathrm{H}_2$ we achieve UCCSD-like accuracy at substantially reduced circuit complexity.
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Quantum Physics · Cross-listed from cond-mat.str-el

Disentangling Tensor Network States with Deep Neural Network

Chaohui Fan, Bo Zhan, Yuntian Gu et al. (+5 more)

We introduce Neural Tensor Network States ($\nu$TNS), a variational many-body wave-function ansatz that integrates deep neural networks with tensor-network architectures. In the $\nu$TNS framework, a neural network serves as a disentangler of the wave-function, transforming the physical degrees of freedom into renormalized variables with much less entanglement. The renormalized state is then efficiently encoded by a back-flow tensor network. This construction yields a compact yet highly expressive representation of strongly correlated quantum states. Using convolutional neural networks combined with matrix product states as a concrete implementation, we obtain state-of-the-art variational energies for the spin-$1/2$ $J_1$-$J_2$ Heisenberg model on the square lattice at the highly frustrated point $J_2/J_1=0.5$, for systems up to $20\times 20$ with periodic boundary conditions. Finite-size scaling of spin, dimer, and plaquette correlations exhibits power-law decay without magnetic or valence-bond long-range order, consistent with a gapless quantum spin-liquid ground state at that point.This $\nu$TNS framework is flexible and naturally extensible to other neural and tensor-network structures, offering a general platform for investigating strongly correlated quantum many-body systems.
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All authors Chaohui Fan, Bo Zhan, Yuntian Gu, Tong Liu, Yantao Wu, Mingpu Qin, Dingshun Lv, Tao Xiang

Quantum Physics

Non-Resonant Boundary Time Crystals from Quantum Synchronization Breakdown

Jun Wang, Shu Yang, Zeqing Wang et al. (+4 more)

Quantum synchronization (QS) in dissipative systems is often inferred from smooth phase locking, leaving open whether its breakdown constitutes a genuine nonequilibrium transition. Here we introduce a Liouvillian framework that classifies driven-dissipative dynamics by the structure of the undriven dissipative background and show that QS breaks down via a Hopf-type dynamical phase transition into a boundary time crystal (BTC). The character of this transition is determined by the background attractor: systems with a self-sustained oscillator (SSO) support robust non-resonant BTCs, whereas those with a polar fixed point (PFP) sustain BTCs only at resonance and lose them under detuning. We identify sharp dynamical and spectral signatures of the QS-BTC transition and thereby establish, within U(1)-symmetric collective-spin Lindbladians driven by a single coherent tone, a background-based allowed/forbidden criterion that unifies QS, its breakdown, and time-crystalline order within a single Liouvillian framework.
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All authors Jun Wang, Shu Yang, Zeqing Wang, Ran Qi, Haiping Hu, Weidong Li, Jianwen Jie

Quantum Physics

Mixed-State Entanglement in a Minimal Model of Quantum Chaos

Tanay Pathak

Understanding the dynamics of quantum correlations in many-body systems is a central problem in non-equilibrium quantum physics. We study the spread of mixed-state entanglement in a minimal model of quantum chaos, the kicked field Ising model. By combining the replica trick with the space-time duality of the model, we determine the exact spectrum of the partially transposed reduced density matrix. The resulting flat spectrum leads to exact relations between entanglement negativity, odd entropy and Rényi mutual information at early times. Numerical results further demonstrate that for equal tri-partitions and at late times, all entanglement measures saturate to the Haar-random values. In contrast, for unequal tri-partitions Rényi mutual information and negativity vanish at late times, implying that the corresponding reduced density matrix is factorizable. Extensive numerical simulations also show that the relation remains quantitatively valid for generic initial states, leading us to conjecture it for all initial states and all times.
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Quantum Physics

Phase-preserving control of Floquet-engineered cavity quantum electrodynamics

J.W. Yu, X.Q. Zhou, Z.B. Ni et al. (+6 more)

We propose a Floquet-engineered framework for the coherent control of the light-matter interaction in a two-level system (TLS) located in a time-modulated cavity. Strictly phase-preserving operation of the TLS-cavity interaction is demonstrated, allowing the interrupt and retrieval of coherent Rabi oscillations without the loss of quantum information. By introducing a phonon reservoir, it is proved that the frequency instability induced from non-Markovian processes does not produce significant phase decoherence during Floquet modulation. Our results provide new insights into the fundamental physics of a driven quantum system and establish Floquet engineering as a powerful tool for coherent quantum information processing.
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All authors J.W. Yu, X.Q. Zhou, Z.B. Ni, X.T. Cheng, Y. Zhao, H.H. Zhu, C.H. Li, F. Liu, C.Y. Jin

Quantum Physics

On aggregation-quantization permutability problem for discrete-time Markov chains

Adam Doliwa, Artur Siemaszko and Adam Zalewski

Given random walk on a graph, the corresponding discrete-time quantum walk can be constructed using the method proposed by Szegedy. On the other hand, given a partition of the set of states of a Markov chain, one can study the corresponding aggregated process. We extend the aggregation technique to the level of quantum Markov chains. We provide conditions under which application of these two operations - Szegedy's quantization and aggregation - give the same result. These consist of the strong lumpability of the underlying Markov chain supplemented by nonlinear relations, generalizing Kolmogorov's cycle condition, that account for the coefficients of both the original and the aggregated transition matrices. In particular, we show that the conditions are satisfied in the case of the random walk on graphs equipped with equitable partitions. We present several examples, which include the classical/quantum walks on Platonic solids. We discuss also relation of discrete-time classical/quantum walks on $N$-dimensional hypercube and the Ehrenfests urn model with $N$ particles. We apply our technique for of discrete-time walks on Cayley graphs of free groups. We also compare our results with those obtained using Cantero-Moral-Velazquez uniformization of unitary matrices.
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Quantum Physics

Multi-qubit controlled gate synthesis without T-count overhead in the small-error limit

Soichiro Yamazaki, Seiseki Akibue and Kaoru Sano

We study the Clifford+T synthesis of quantum multiplexers $U=\bigoplus_{i=1}^{2^n}U_i$: an $n$-qubit control register selects which single-qubit gate $U_i\in\mathrm{SU}(2)$ acts on the target qubit. For each block $U_i$, consider the minimum even T-count needed to approximate it within diamond distance $\varepsilon$ without ancillae, and let $m$ be the largest of these costs. For an arbitrary multiplexer $U$, we construct an approximation of $U$ within the same distance using at most $m+O(\sqrt{2^n(m+1)})$ $T$ gates. With one control qubit, the cost is $m+O(1)$ and no ancillae are required. We also prove a lower bound that allows the Clifford+T circuit to use any number of clean ancillae initialized to zero and returned exactly to zero. For fixed $n$ and independent Haar-random blocks, the minimum T-count among these circuits lies between $(3-\delta)\log_2(1/\varepsilon)$ and $(3+\delta)\log_2(1/\varepsilon)$ for every fixed $\delta>0$, except with probability $O(\varepsilon^{c_{n,\delta}})$ as $\varepsilon\rightarrow0$. The optimal leading coefficient is therefore the same as for a single Haar-random $\mathrm{SU}(2)$ gate. In the lower-bound proof, unitarity forces pairs of off-diagonal blocks describing transitions in opposite directions to satisfy cancellation relations with residuals of order $\varepsilon^2$. We combine these relations with the arithmetic of Clifford+T circuits to bound the Haar measure of targets compatible with each pair of off-diagonal blocks. As an application, we obtain ancilla-free approximations of Haar-random $\mathrm{SU}(4)$ gates within diamond distance $\varepsilon$, using at most $(9+\delta)\log_2(1/\varepsilon)$ $T$ gates for every fixed $\delta>0$, except with probability $O(\varepsilon^{c_{\delta}})$ with $c_{\delta}>0$.
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Quantum Physics

Frequency-resolved N-photon correlations in the ultra-strong coupling regime

Wen Huang, Qian Bin, Ying Wu et al. (+1 more)

Frequency-resolved photon emission is central to applications from quantum information encoding to high-resolution spectroscopy, and then studying their correlations is therefore essential for revealing the underlying emission pathways and multiphoton statistics. Here, we investigate frequency-resolved N-photon correlations in an ultrastrongly coupled cavity QED system where a qubit interacts with a single-mode cavity. Owing to counter-rotating interactions, the eigenstates and energy spectrum are strongly modified, giving rise to rich spectral and statistical properties in the emitted frequency-resolved photons. Through frequency-selective detection, we reveal pronounced multiphoton antibunching, as well as multiphoton bunching originating from cascade transitions among dressed eigenstates. In particular, we show that parity symmetry plays a decisive role in shaping these correlations. The symmetry-breaking opens additional transition channels and dramatically enhances the generation of correlated photon pairs and even photon triplets of different frequencies. Our work extends frequency-resolved correlations to the ultra-strong coupling regime and demonstrates their potential as a sensitive probe of symmetry in light-matter interaction systems.
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All authors Wen Huang, Qian Bin, Ying Wu, Xin-You Lü

Quantum Physics · Cross-listed from cond-mat.mtrl-sci

Emergent giant topological Hall effect in twisted Fe3GeTe2 metallic system

Hyuncheol Kim, Kai-Xuan Zhang, Yu-Hang Li et al. (+3 more)

The topological Hall effect, driven by the exchange interaction between conduction electrons and topological magnetic textures such as skyrmions, is a powerful probe for investigating the topological properties of magnetic materials. Typically, this phenomenon arises in systems with broken global inversion symmetry, where Dzyaloshinskii-Moriya interactions stabilize such textures. Here, we report the discovery of an emergent giant topological Hall effect in the twisted Fe3GeTe2 metallic system, which notably preserves the general global inversion symmetry. This effect manifests exclusively within a narrow window of "magic" twist angles ranging from 0.45{\deg} to 0.75{\deg}, while it is absent identically outside of that range, highlighting its unique and emergent nature. Micromagnetic simulations reveal that this topological Hall effect originates from a skyrmion lattice induced by alternating in-plane and layer-contrasting Dzyaloshinskii-Moriya interactions that result from local inversion symmetry breaking. Our findings underscore twisted Fe3GeTe2 as a versatile platform for engineering and controlling topological magnetic textures in metallic twisted van der Waals magnets, thereby opening up new avenues for next-generation spintronic devices.
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All authors Hyuncheol Kim, Kai-Xuan Zhang, Yu-Hang Li, Giung Park, Ran Cheng, Je-Geun Park

Saturday 14 March

Quantum Physics · Cross-listed from physics.chem-ph

The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project

Qiming Sun, Matthew R Hermes, Xiaojie Wu et al. (+100 more)

Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum chemical method development. This article reviews the major advances since the previous overview in 2020, covering new modules and methodology, infrastructure changes, and performance benchmarks.
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All authors Qiming Sun, Matthew R Hermes, Xiaojie Wu, Huanchen Zhai, Xing Zhang, Abdelrahman M. Ahmed, Juan José Aucar, Oliver J. Backhouse, Samragni Banerjee, Peng Bao, Nikolay A. Bogdanov, Kyle Bystrom, Frédéric Chapoton, Ning-Yuan Chen, Ivan Yu. Chernyshov, Helen S. Clifford, Sander Cohen-Janes, Zhi-Hao Cui, Yann D. Damour, Nike Dattani, Linus Bjarne Dittmer, Sebastian Ehlert, Janus Juul Eriksen, Francesco A. Evangelista, Simon A. Ewing, Ardavan Farahvash, Kevin Focke, Yang Gao, Kevin E. Gasperich, Nathan Gillispie, Jonas Greiner, Matthew R. Hennefarth, Jan Hermann, Christopher Hillenbrand, Joonatan Huhtasalo, Basil Ibrahim, Bhavnesh Jangid, Alireza Nejati Javaremi, Andrew J. Jenkins, Yu Jin, Daniel S. King, Derk Pieter Kooi, Jo S. Kurian, Henrik R. Larsson, Bryan Tak Gwong Lau, Seunghoon Lee, Susi Lehtola, Chenghan Li, Hao Li, Jiachen Li, Rui Li, Shuhang Li, Aleksandr O. Lykhin, Ankit Mahajan, Nastasia Mauger, Pablo del Mazo-Sevillano, Jonathan Moussa, Kousuke Nakano, Verena A. Neufeld, Linqing Peng, Hung Q. Pham, Peter Pinski, Pavel Pokhilko, Zhichen Pu, Yubing Qian, Stephen Jon Quiton, Wanja T. Schulze, Thais R. Scott, Aniruddha Seal, James D. Serna, James E. T. Smith, Kori E. Smyser, Terrence Stahl, Chong Sun, Kevin J. Sung, Egor Trushin, Shiv Upadhyay, Ethan A. Vo, Thijs Vogels, Shirong Wang, Tai Wang, Xiao Wang, Xubo Wang, Yuanheng Wang, Mark Williamson, Junjie Yang, Hong-Zhou Ye, Chia-Nan Yeh, Haiyang Yu, Jincheng Yu, Victor Wen-zhe Yu, Chaoqun Zhang, Dayou Zhang, Yichi Zhang, Zijun Zhao, Zehao Zhou, Andrew J. Zhu, Tianyu Zhu, Timothy C. Berkelbach, Laura Gagliardi, Sandeep Sharma, Alexander Sokolov, Garnet Kin-Lic Chan

Quantum Physics

Fast Single Nitrogen-Vacancy Center Ramsey Characterization using a Physics-Informed Neural Network

Chao Shang and Gregory D. Fuchs

Precise characterization of the local spin environment of single diamond nitrogen-vacancy (NV) centers is crucial for advancing quantum sensing, quantum networking, and the optimization of quantum materials. However, single NV center fluorescence measurements requires long averaging times to obtain clean data that is suitable for conventional model fitting, and that constitutes a key experimental bottleneck for high-throughput characterization. To address this, we introduce NVRNet, a physics-informed simulation-to-reality machine learning pipeline that maps minimal-sweep, noisy Ramsey data to a denoised waveform while directly estimating the hyperfine coupling to proximal ${}^{13}\mathrm{C}$ nuclear spins. The pipeline's denoiser utilizes a two-stage time-frequency U-Net and an attention-augmented time-domain U-Net, pretrained on Hamiltonian-based spin-dynamics simulations with experimentally calibrated noise. To effectively bridge the simulation-to-reality gap, parameter-efficient adapters are attached to the backbone and fine-tuned on targeted experimental data. Across three distinct NV centers, this experimentally fine-tuned model reduces the median reconstruction error on held-out, few-sweep traces to $0.44\text{-}0.67\times$ of the raw experimental noise level. Subsequently, a transformer-based estimator extracts the underlying hyperfine parameters. Forward reconstructions derived from these inferred parameters faithfully reproduce the dominant experimental time- and frequency-domain features, yielding representative normalized fast Fourier transform (FFT) reconstruction errors of $0.10\text{-}0.19$. By reducing both the required data volume and acquisition time, NVRNet enables up to $\sim 40\times$ acceleration of the measurement process, establishing a fast, hardware-compatible pathway for robust hyperfine inference and autonomous qubit characterization.
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Quantum Physics

Finite path integrals on stochastic branched structures

Roukaya Dekhil, Clifford Ellgen and Bruno Klajn

In this paper, we present a statistical model of spacetime trajectories based on a finite collection of paths organized into a branched manifold. For each configuration of the branched manifold, we define a Shannon entropy. Given the variational nature of both the action in physics and the entropy in statistical mechanics, we explore the hypothesis that the classical action is proportional to this entropy. Under this assumption, we derive a Wick-rotated version of the path integral that remains finite and exhibits both quantum interference at the microscopic level and classical determinism at the macroscopic scale. In effect, this version of the path integral differs from the standard one because it assigns weights of non-uniform magnitude to different paths. The model suggests that wave function collapse can be interpreted as a consequence of entropy maximization. Although still idealized, this framework provides a possible route toward unifying quantum and classical descriptions within a common finite-entropy structure.
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Quantum Physics

Practical Limits to Single-Mode Vacuum Squeezing with a SNAIL Parametric Amplifier

Theodore Shaw, Debsuvra Mukhopadhyay, Zhuoqun Hao et al. (+4 more)

We characterize single-mode vacuum squeezing generated by a SNAIL Parametric Amplifier (SPA) operated under conditions representative of practical sensing and qubit-readout experiments. Motivated by prior expectations that Kerr-induced distortion limits squeezing in degenerate parametric amplifiers, we studied squeezing as a function of external flux and pump power to explore operating points where Kerr nonlinearity is theoretically minimized. We find that for squeezing operation at a fixed frequency, Kerr varied by about a factor of two and the achievable squeezing showed no significant dependence on Kerr. Rather than Kerr, the squeezing is dominated by internal resonator loss and insertion loss in the microwave chain as confirmed by theoretical modeling. These results indicate that, in practical SPAs, reducing loss, rather than suppressing Kerr, is the primary route to improved squeezing performance.
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All authors Theodore Shaw, Debsuvra Mukhopadhyay, Zhuoqun Hao, Josiah Cochran, Haley Cole, Archana Kamal, Shyam Shankar