2377 papers
Statistical mechanics explores how the chaotic motion of countless tiny particles gives rise to the predictable laws governing heat, pressure, and phase transitions. This field bridges the gap between the microscopic world of atoms and the macroscopic reality we experience daily, offering deep insights into why materials behave the way they do.
On Gist.Science, we process every new preprint in this category as it appears on arXiv to make these complex findings accessible to everyone. For each paper, we provide both a plain-language explanation for the curious reader and a detailed technical summary for specialists, ensuring that groundbreaking research is never lost behind a wall of jargon.
Below are the latest papers in statistical mechanics, freshly curated and summarized to help you understand the cutting edge of this fascinating discipline.
This paper completes the phase diagram of the driven Curie-Weiss model by identifying a coexistence regime of paramagnetic and ferromagnetic phases and characterizing the dynamical criticality of its nonequilibrium specific heat, which exhibits asymmetric critical exponents and a driving-dependent Curie temperature distinct from thermal equilibrium behavior.
This paper proposes LNS-VT, a novel Ising-machine-assisted Large Neighborhood Search method that introduces a tunable parameter for the number of consecutive re-optimized steps per vehicle to finely control subproblem size while preserving feasibility, thereby significantly improving solution quality for the Vehicle Routing Problem and demonstrating the importance of subproblem-size control for other combinatorial optimization tasks.
This paper develops a comprehensive nonequilibrium nucleation theory (NNT) for systems with non-conserved order parameters by deriving the dynamics of droplet formation through stochastic projection and action minimization, revealing that the nucleation barrier differs from time-reversed relaxation paths and validating this framework against numerical simulations in active matter and population dynamics models.
This paper utilizes a random matrix ensemble to demonstrate that the complex spectra of unphysical denoiser channels used in probabilistic error cancellation inherit their structure from random Lindbladians, with noise locality introducing a hierarchy of timescales.
This paper establishes a thermodynamic framework for non-equilibrium jump diffusions on by decomposing their generator into symmetric and anti-symmetric parts relative to the invariant measure, thereby deriving a complete free energy dissipation formula that separates entropy production from housekeeping heat and clarifies the structure of non-equilibrium stationary states.
This paper utilizes the integrability of the large- limit to derive exact resonance conditions and a reduced Hamiltonian for the long-range quantum model, revealing how parametric resonances on mesoscopic timescales drive nonlinear dynamics, enhance entanglement growth, and generate spatially modulated correlations that deviate from the mean-field limit.
This paper presents a geometric optimization framework in the plane of normalized branch dissipations that transforms the problem of maximizing efficiency at fixed power for Carnot-like heat engines with power-law dissipation into a linear programming problem, thereby deriving the exact power-efficiency bounds.
This review article introduces the fuzzy sphere regularization method as an efficient tool for studying 3D conformal field theories and critical phenomena, highlighting its unique ability to reveal deep connections between noncommutative geometry, the quantum Hall effect, and the state-operator correspondence on the geometry.
This paper theoretically derives and experimentally validates the first passage time distribution for an underdamped harmonic oscillator using a combination of Kramers operator eigenvalue analysis and Hamiltonian approximation, demonstrating its utility for precisely estimating the power of information engines.
This paper derives the first passage time distribution for an underdamped harmonic oscillator crossing a threshold by employing energy diffusion, eigenvalue analysis, and Hamiltonian approximations across different quality factors, all of which show excellent agreement with numerical simulations and reveal a specific noise-driven shape in the mean trajectories.