2356 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 study demonstrates that non-Abelian vortex dynamics in spin-2 Bose-Einstein condensates fundamentally govern turbulent mass flow organization, producing a unique anomalous mass-current spectrum that vanishes and reverts to the standard scaling when non-Abelian interactions are restricted.
This paper employs a flat histogram algorithm with cluster moves to demonstrate that hard core lattice gas models on a triangular lattice with exclusion up to the seventh next-nearest neighbor () undergo a single, discontinuous freezing phase transition from a fluid to a sublattice-ordered phase, providing precise determinations of their critical parameters.
This paper reports the experimental realization of a non-Hermitian phase transition in the bulk ferromagnetic semiconductor EuO, where optical excitation induces a qualitative shift in relaxation dynamics from bi-exponential real to single-exponential complex decay near an exceptional point, offering a new mechanism to control bulk-dynamic properties in condensed-matter systems.
This paper applies statistical mechanics and replica theory to model semantic compression as a spin glass system, revealing distinct phase transitions between paraphrase emergence and compression types while demonstrating that efficient algorithms can achieve near-optimal performance in typical cases despite the problem's worst-case computational hardness.
This paper demonstrates that in Kuramoto models, weak higher-order interactions enhance synchronization while strong ones hinder it, revealing that a mixed allocation of pairwise and higher-order couplings optimizes collective dynamics under constrained interaction budgets.
This paper introduces a data-driven approach using intrinsic dimension to characterize the complexity of quantum trajectories in open systems, revealing how conservation laws and dynamical constraints like integrability and Hilbert-space fragmentation lead to pronounced reductions in complexity amidst typically chaotic Lindblad evolution.
This paper introduces a parameter-free free-energy functional that unifies the formation of disordered hyperuniform labyrinthine structures in soft matter and the cosmic web in an expanding universe, demonstrating that both phenomena arise from the same underlying physics where long-wavelength fluctuations are inherited from initial conditions rather than generated by dynamics.
This paper introduces a Gaussian field formalism to compute mutual information for general spacetime regions, demonstrating that regions with identical causal completions yield the same mutual information and providing numerical verification of the timelike tube theorem while establishing a practical framework for studying entanglement in generalized free field theories.
This introductory review bridges a gap in graduate-level literature by presenting statistical physics and sociophysics models for fracture mechanics and earthquake dynamics, highlighting the transition from classical theories to modern applications of inequality measures in predicting large-scale failures.
This paper demonstrates that the mean and fluctuations of observed currents in a driven system can certify the total hidden dissipation, including energy lost on unobserved transitions, by leveraging a cycle-observability condition that treats partial observation as a minimum-energy completion problem over unseen cycles.