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 presents the first proof of a random-matrix spectral ramp in a static, geometrically local many-body Hamiltonian by embedding the Floquet quasienergy spectrum of a dual-unitary circuit into a time-independent system using a variant of the Feynman-Kitaev clock construction.
This paper revises the seminal theory of Ovchinnikov and Erikhman regarding ionic-motion-induced decoherence to correct an oversight, thereby establishing the precise conditions and length scales up which electrons in a macroscopic crystal lattice can be treated as a closed quantum system.
This paper presents a numerical study using the adaptive second-order Kuramoto model on a European power grid to demonstrate that while adaptive High Voltage Direct Current (HVDC) lines improve steady-state synchronization and reduce cascade sizes, they also introduce drawbacks such as frequency spread, Braess effects, and significantly longer relaxation times.
This paper addresses the gap in modeling stiff forces in soft matter systems by providing a practical summary of constrained Brownian dynamics equations with "soft" constraints and a novel singular perturbation derivation that validates their use over relevant timescales, while also extending the framework to scenarios with spatially varying mobility.
This paper introduces a counterwork functional derived from a sign-inverting memory-filtered protocol that satisfies a reciprocal Jarzynski equality with the original work, establishing that the sum of their average values is non-negative and that robust strategies under incomplete information should prioritize endpoint reversal while minimizing dissipated counterwork.
This paper introduces a tractable mean-field model demonstrating how self-organized robustness emerges in interacting systems through meta-optimization, resulting in a dynamically modulated "seascape" that accelerates relaxation via optimized Wasserstein gradient flow and functions as a hierarchical associative memory.
Using large-deviation theory, this paper explains how weak explicit symmetry breaking leads to an exponential suppression of topological defect formation during non-equilibrium phase transitions by showing that defects arise from rare fluctuations, a mechanism validated by simulations of stochastic Ginzburg-Landau models.
This paper presents a finite element framework for simulating thermal fluctuations in compressible fluids that preserves the fluctuation-dissipation balance at the discrete level through a stochastic weak formulation and nodal quadrature, validated across one, two, and three dimensions.
Using density matrix renormalization group calculations, this study reveals that a frustrated four-leg spin-1/2 ladder exhibits distinct short-range antiferromagnetic, ferromagnetic, and effective spin-2 regimes, clarifying how the interplay between two coupled two-leg ladders drives transitions between trivial and Haldane phases and the emergence of spin-2 behavior.
This paper establishes that the static correlation properties of mixed-state phases in long-range Lindbladian systems, specifically the polynomial decay of mutual and conditional mutual information, arise naturally from dynamical features like rapid mixing and frustration-freeness, thereby extending Markov property results to long-range regimes relevant for experimental platforms.