250 papers
This paper introduces a robust quantum algorithm that estimates the density of states for fermionic systems within specific particle-number subspaces by evolving random initial states, offering a practical pathway to achieve early quantum advantage through noise-resilient, semi-quantitative reconstructions compatible with both NISQ and fault-tolerant devices.
This paper investigates the functional-diffusion of magnetization in an Ising model with an external field, revealing power-law anomalies in the approach to ergodicity across various temperatures and fields through both numerical simulations and exact solutions.
This paper establishes that the extreme value statistics of non-stationary, recurrent systems governed by infinite ergodic theory and an infinite invariant density are determined by the return exponent and the infinite measure, leading to a distinct universality class that deviates from the classical Fréchet, Gumbel, and Weibull distributions.
This study uses Monte Carlo simulations to demonstrate that quasi-three-dimensional stick percolation systems, despite having a higher percolation threshold than their two-dimensional counterparts, share the same universal finite-size scaling function as 2D continuum and lattice percolation.
This paper reformulates the concept of neutral wealth taxation as a drift-shift symmetry in stochastic wealth dynamics, demonstrating that while a proportional tax preserves the underlying statistical structure of wealth distribution, practical implementation failures correspond to specific violations of this symmetry that introduce new, non-neutral physical effects.
This paper validates the Relevance-Resolution framework as a robust unsupervised method for identifying optimal low-resolution representations of high-dimensional data, demonstrating that its information-theoretic criteria consistently align with ground-truth Kullback-Leibler divergence minimization across diverse synthetic and physical datasets.
This paper introduces a novel entropy production estimator for continuous systems with limited resolution that relies solely on the frequency and duration of particle transitions across spatial regions, eliminating the need for Markovian events or discrete underlying dynamics.
This paper demonstrates that Boltzmann Generators can effectively sample the liquid-gas critical point of a Lennard-Jones fluid and capture critical signatures, though their current utility is constrained by small system sizes that suppress large-scale fluctuations.
This paper develops a perturbative framework based on the Fokker-Planck equation to derive an explicit analytical expression for the mean-squared displacement of active Brownian particles with finite rotational inertia, a result that is validated through numerical simulations.
This paper proposes a universal framework explaining quadrupolar order in magneto-electric materials as a composite phase emerging from a parent state driven by thermal fluctuations and symmetry, offering a predictive approach for transition temperatures and strain coupling without requiring explicit microscopic details.
Although power-counting suggests that spatially inhomogeneous diffusion is irrelevant in the contact process, large-scale simulations reveal that such disorder destabilizes the standard directed-percolation critical point by generating effective random-mass disorder, thereby driving the transition into an infinite-randomness universality class.
This paper explores the statistical mechanics of particles in indistinguishable energy states by adapting combinatorial counting methods to derive exact distribution functions, revealing that classical particles within this framework exhibit a definitive glass transition characterized by the vanishing of configurational entropy below a finite temperature.
This study employs Monte Carlo simulations to investigate how nonmagnetic impurities and quenched random magnetic fields suppress the antiferromagnetic phase transition in Ising metamagnets, revealing distinct linear and nonlinear dependencies of the critical temperature on disorder concentration and field width, respectively, while confirming that the pure system's Néel temperature is recovered in the limit of vanishing disorder.
This study utilizes classical Monte Carlo simulations of an effective quadrupole model on a diamond lattice to demonstrate that the competition between magnetic fields and quadrupole anisotropy, mediated by a crucial symmetry-allowed biquadratic interaction, drives successive single- and double- ordering transitions that reproduce the experimentally observed weak-field topology in PrIrZn.
This paper proposes and analyzes a low-voltage error-suppression technique for stochastic CMOS bits by coupling them into chains, demonstrating via tensor network simulations that while inter-unit correlations enhance reliability, increasing bias voltage remains a more energy-efficient path to stability than extending chain length.
This paper resolves the controversy of spurious multifractality in discrete systems by establishing a rigorous Finite-Size Scaling protocol for MFDFA on the 2D Ising model, demonstrating that apparent multifractality in clean systems is a finite-size artifact while genuine multifractality persists in disordered variants like the Random Bond Ising Model.
Zeitz, Wolf, and Stark demonstrate that while active and Brownian particles exhibit similar subdiffusive behavior near the percolation threshold in a random Lorentz gas, active particles reach steady state faster and display lower effective diffusion at high activity due to self-trapping effects.
This paper challenges the notion of universal monotonic entropy increase by demonstrating that time-reversal invariance necessitates a constant entropy trajectory, proposing instead that entropy is a stochastic variable whose distribution is fundamentally reshaped by constraints and boundary conditions rather than by an intrinsic directional drive.
This paper introduces a gradient-based optimization method using straight-through Gumbel-Softmax estimation to enable efficient parameter inference and inverse design in exact stochastic kinetic models by approximating gradients through continuous relaxation while preserving discrete stochastic dynamics in the forward pass.
This paper derives Navier-Stokes hydrodynamic equations and calculates transport coefficients for confined, quasi-two-dimensional mixtures of inelastic hard spheres at moderate densities using the revised Enskog theory, applying the results to analyze thermal diffusion-driven segregation.