2422 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 investigates generalized geometric Brownian motion models, particularly those arising in turbulence theory, to demonstrate how the existence of a standard invariant measure depends on drift, diffusion, and discretization, while proposing the concept of infinite ergodicity to address cases where such a measure fails to exist.
This review synthesizes current understanding of anomalous energy transport in Fermi-Pasta-Ulam-Tsingou chains, distinguishing between the and scaling universality classes while addressing how finite-size effects, conservative noise, and proximity to integrable limits influence the transition from diffusive to anomalous hydrodynamic regimes.
This paper demonstrates that for an ensemble of independent finite-speed searchers, the mean fastest first-passage time to a target is bounded below by the minimal ballistic travel time and converges exponentially to this limit as the number of searchers increases, revealing a significant efficiency advantage over Brownian searchers and correcting misconceptions about short-time behavior in diffusive models.
This paper investigates a one-dimensional model of a self-phoretic particle, such as a camphor grain, which transitions from a stationary state to regular oscillatory motion due to chemical field reflections in a confined channel, with the authors providing analytical phase diagrams, frequency/amplitude derivations, and a mechanism for particle reflection near channel boundaries.
This paper generalizes the Loschmidt echo and out-of-time-order correlator to open quantum systems under Lindblad dynamics, revealing universal scrambling behaviors across dissipation regimes, establishing a link between OTOC and Rényi entropy, and proposing an experimental protocol for measurement.
This paper demonstrates that while super-Gibbs phase coexistence in multicomponent mixtures is achievable in the grandcanonical ensemble through interaction tuning, it is not automatically realized in the experimentally relevant canonical ensemble due to interfacial tension constraints, but a graph-theoretical approach can identify the necessary conditions to restore ensemble equivalence.
This paper extends the study of Floquet Conformal Field Theories to higher dimensions by utilizing quaternionic representations to classify dynamical phases in multi-step drive protocols, revealing a fundamental geometric correspondence where heating, critical, and non-heating regimes map to the presence or absence of non-extremal and extremal Killing horizons in the system's base and dual AdS spaces.
This paper utilizes an effective theory of dynamic critical phenomena to demonstrate that the photon emission rate near the QCD critical point diverges with the correlation length and follows a universal spectrum, reflecting the nonequilibrium properties of the near-critical liquid.
This paper demonstrates that the multiscale complexity formalism, specifically the complexity profile, effectively characterizes the critical transition and emergent magnetic domain structures in two-dimensional Ising systems by identifying unique information-theoretic signatures in the critical region and bounded pairwise complexity in the disordered phase.
This paper presents a statistical-mechanical analysis of a random planting model with growing hard disks, demonstrating that its nonequilibrium steady state can be mapped to a nonadditive polydisperse hard-disk fluid to derive analytical predictions for plant density and spatial organization that align with numerical simulations.