2446 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 demonstrates through numerical analysis that classical one-dimensional systems invariably exhibit anomalous heat conductivity diverging with system size, even in cases where previous studies suggested Fourier's law held, by showing that a hydrodynamic component eventually dominates the energy flux despite potentially occurring at extremely large scales.
This paper demonstrates that pump-probe experiments can uniquely identify 2D topological excitations in 3D layered spin liquids by revealing distinct subdiffusive spreading and anomalous decay laws, such as logarithmic propagation and a density decay, which arise from the topological constraint that only pairs of fractionalized excitations can hop between layers.
This paper demonstrates that timelike entanglement measures derived from the spacetime density kernel in the Rosenzweig-Porter model, including Tsallis entropy, imagitivity, and a newly defined kernel negativity, serve as sharp diagnostics for distinguishing between ergodic, fractal, and localized phases by exhibiting distinct growth patterns, spectral form factor-like structures, and correlations with fractal dimensions.
The paper introduces GG-PI, a computationally efficient framework that leverages generative modeling and Gibbs sampling on classical simulation data to accurately recover nuclear quantum effects and transfer across temperatures without retraining, significantly outperforming traditional path integral molecular dynamics.
Using the Random Phase Approximation, this study reveals that while bias-driven critical charge fluctuations in an interacting quantum dot can be described by an effective temperature, current fluctuations exhibit genuinely non-equilibrium behavior with a negative fluctuation-dissipation ratio, establishing current noise as a sensitive probe for non-equilibrium quantum phase transitions.
This paper establishes an explicit link between molecular detailed balance breaking and active fluctuations in a minimal gel model, deriving fluctuating hydrodynamic equations that predict tracer motion to complement the fluctuation-dissipation theorem with a fluctuation-activity relation for nonequilibrium biological systems.
This paper establishes a deep connection between fracton order and product codes by demonstrating how specific classical seed codes can systematically generate both Type-I and Type-II fracton models in nonlocal and local constructions, including examples on irregular graphs and planar aperiodic tilings.
This paper proposes a framework for modeling non-equilibrium and self-organizing systems using generative models and the variational free energy principle, which offers a tractable, parsimonious explanation of system dynamics as a form of variational inference without requiring the system to literally perform inference.
This paper provides a rigorous mathematical justification for the energy-independent relaxation time approximation in hard interactions, proposes a method to restore collision invariance, and elucidates how interaction types (hard versus soft) and physical parameters determine the non-analytical structures, such as hydrodynamic poles or gapless branch-cuts, in retarded correlators.
This paper revisits the fuzzy sphere regulator for the 3D Ising model by utilizing Conformal Perturbation Theory to systematically analyze finite-size corrections and develop a novel method for extracting Operator Product Expansion coefficients from energy level sensitivities, thereby refining the connection between numerical lattice results and Conformal Field Theory predictions.