1593 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 presents a two-loop perturbative method to compute the family of probability distributions for the model's order parameter, indexed by the ratio of system size to correlation length, and validates these results against Monte Carlo simulations and Functional Renormalization Group data.
This paper demonstrates that the voter model exhibits aging behavior and dynamical scaling functions consistent with the non-equilibrium Schrödinger algebra, providing a paradigm for relaxation in critical dynamics without detailed balance.
This paper derives exact fluctuation-response relations for Gaussian macroscopic systems to reconstruct linearized dynamics and diffusion matrices, applying this framework to gene regulatory networks to provide an explicit decomposition of internal and external noise.
This paper develops a topological holographic framework to classify average categorical symmetries and symmetry-protected topological (SPT) phases in one-dimensional disordered systems, demonstrating that average anomalies lead to long-range entanglement and exotic low-energy behavior.
This paper develops a parameterized equation of state based on a new potential energy landscape theory that accurately describes the pressure, compressibility, and thermodynamic properties of hard sphere systems across the fluid, metastable, and glassy regions, while also identifying the breakdown of standard transport property scaling laws.
This paper demonstrates that the interplay between the Weibull modulus (disorder) and the slenderness ratio (geometry) determines whether disorder is suppressed or expressed globally in lattice fractures, revealing that disorder-induced toughening is a non-monotonic phenomenon that cannot be explained solely by crack tortuosity or damage levels.
This paper introduces a lattice model of a chiral random walk that bridges classical stochastic diffusion and quantum evolution, demonstrating that the topological protection of edge currents persists from the unitary quantum limit into the dissipative classical regime.
This paper demonstrates that binary autoencoders improve the efficiency of FMQA-based black-box optimization by learning latent representations that better preserve the original problem's feasibility, neighborhood structure, and geometric properties compared to manual encodings.
This paper uses discrete element method simulations and -rheology continuum modeling to demonstrate that the velocity profile and surface flow layer thickness in rotating drums follow specific scaling laws derived through dimensional analysis.
This paper investigates how spatially or temporally non-uniform error rates—specifically those caused by rare, extended events like cosmic rays—affect quantum error correction, finding that while such events create a "Griffiths phase" with stretched-exponential failure rates in 1D repetition codes, they lead to a total loss of threshold in 2D toric codes.