1089 papers
This paper extends semi-classical instanton analysis to a symmetric quartic potential with four degenerate minima, deriving energy splittings and Rabi oscillations for distinct tunneling pathways that show excellent agreement with numerical results while revealing a critical coupling regime where the discrete symmetry melts into a continuous symmetry.
This paper proposes a broadband impedance matching network utilizing the negative inductance of a biased Josephson junction to overcome the gain-bandwidth limitations of passive circuits, thereby enhancing the scan rate for axion dark matter searches.
This paper resolves a 20-year-old conjecture by proving that the volume-averaged Ricci scalar of binary Bayesian networks is universally quantized to positive half-integers for tree and complete-graph structures via a Beta function cancellation mechanism, while demonstrating that this quantization fails in general due to loop counterexamples and contrasting the positive curvature of discrete networks with the negative curvature of Gaussian DAGs.
This paper proposes a multi-stage residual learning framework for quantum machine learning models to mitigate the inherent bias against learning high-frequency or non-dominant frequency components, demonstrating significant improvements in spectral expressivity and test performance across diverse synthetic benchmarks.
This paper introduces an extension of localized intrinsic bond orbitals (IBOs) to decode correlated charge migration dynamics, successfully mapping complex many-electron behaviors to intuitive chemical concepts like curly arrows and hyperconjugation while identifying key mechanisms and efficient molecules through high-level TDDMRG simulations.
This paper introduces a fully digital protocol utilizing local projective measurements and unitary feedback to efficiently prepare algebraically correlated, a priori unknown ground states of frustration-free gapless quantum systems, with performance verified across various models and shown to reveal universal critical properties through transient cooling dynamics.
This paper introduces Regularized Warm-Started QAOA (RWS-QAOA), a protocol that combines a classical warm start with fixed-parameter constant-depth quantum circuits to outperform strong classical solvers on the Max-Cut problem, demonstrating superior performance on 96-node hardware and projecting a quantum advantage crossover for 3,000-node graphs with fewer than 1.3 million physical qubits.
This paper argues that quantum trajectories in the de Broglie-Bohm formulation are unsuitable for semiclassical approximations because their chaotic behavior and lack of integrability, even in systems where classical motion is regular, fail to preserve the correspondence necessary to clarify the classical-quantum transition.
This paper introduces a low-overhead approach to reduce bias in quantum error mitigation by constructing verifiable benchmark circuits that mirror application noise profiles, demonstrating up to 15% fidelity improvements on 100-qubit circuits through a new method called benchmarked-noise zero-noise extrapolation (bnZNE).
This paper constructs the Gamow Golden Rule for multichannel scattering to derive decay distributions, partial decay constants, widths, and branching fractions for resonances with multiple decay modes, demonstrating the theory's application through two coupled-channel square well potentials.
This paper proposes a variational quantum sensing framework that utilizes a quantum circuit-optimized probe to learn environmental features from radio-frequency signals, demonstrating through ray-tracing simulations that this approach enables robust localization with no deployment channel measurements and superior sensitivity to weak or obstructed signals compared to classical baselines.
This paper presents a computationally efficient theoretical framework based on the Power-Zienau-Woolley Hamiltonian and maximally localized Wannier functions that accurately captures light-matter interactions beyond the electric-dipole approximation in extended systems without requiring finite-order multipole expansions, thereby enabling precise first-principles simulations of spatially structured light dynamics in nanoscale materials.
This study demonstrates that quantum entanglement serves as a functional resource in competitive reinforcement learning, enabling hybrid quantum-classical agents trained on the game Pong to consistently outperform separable quantum circuits and match or exceed classical baselines by learning structurally distinct features that better model dynamic agent interactions.
This paper resolves a conjecture by Hanotel and Loubenets by proving that all bipartite states on , whether pure or mixed, satisfy the CHSH inequality when restricted to spin-1 observables.
The paper introduces Geo-ADAPT-VQE, a geometry-aware adaptive variational quantum eigensolver that utilizes natural gradients for operator selection to achieve faster, more stable convergence and significantly shorter ansatz circuits compared to existing gradient-based methods.
This paper demonstrates that machine learning algorithms, including unsupervised clustering and convolutional neural networks, can successfully identify the thermodynamic arrow of time and distinguish between forward and time-reversed unitary evolutions in a ten-qubit nitrogen-vacancy center quantum processor by analyzing single trajectories with projective measurements.
This paper analytically derives and proves a tight quantum speed limit for the charging of an -qubit Dicke quantum battery, establishing that the minimum time to reach a normalized ergotropy is bounded by , where the bound is saturated at small ergotropy values and governed by a unique composite figure of merit.
This paper demonstrates that the thermal susceptibility of quantum coherence in multipartite systems depends critically on both the environmental configuration and the internal state architecture, revealing that while local dephasing universally accelerates decoherence, common structured reservoirs can preserve coherence in specific states like -class and certain Werner mixtures, thereby enabling coherence dynamics to serve as a sensitive probe for finite-temperature environments and a basis for quantum thermometry.
This paper identifies extrinsic population dynamics as the fundamental cause of discrepancies between theoretical and experimental lifetime estimates in multilevel systems, proposing a revised readout protocol and an integrated theory that successfully explains recent spin-valley measurements in bilayer graphene.
This paper experimentally demonstrates that while tuning modulation variance or adding detector loss can extend the operational distance of continuous-variable quantum key distribution (CV-QKD) with constant-rate error correction, rate-adaptive forward error correction is the superior strategy for maintaining high secret key rates across a wide range of distances.