1558 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 introduces a novel simulation technique combining isobaric Lattice Switch Monte Carlo and thermodynamic integration to accurately calculate free energy differences and coexistence pressures between clathrate hydrate structures II and H, yielding results that align well with experimental data for argon and methane systems.
This paper derives the asymptotic first passage time distribution for space-dependent variable-order time-fractional diffusion, demonstrating that the survival probability decays as where is the minimum fractional exponent, a theoretical prediction validated by exact solutions and Monte Carlo simulations that enables the identification of spatially heterogeneous anomalous transport.
By combining high-speed X-ray tomography with a non-equilibrium statistical framework that draws an analogy to hard-sphere liquids, this paper establishes a unified, microscopically-based constitutive law for dense granular flows that resolves the limitations of the traditional rheology across quasi-static to inertial regimes.
This paper employs stochastic density functional theory to extend the classical Debye-Falkenhagen prediction of frequency-dependent conductivity from dilute to concentrated electrolytes by incorporating hard-core repulsion effects, while also addressing the challenges in experimentally observing this phenomenon.
This paper proposes diabatic quantum annealing as a controllable, purely unitary alternative to traditional quantum annealing for Boltzmann sampling, demonstrating that the effective temperature can be precisely tuned via the annealing rate to achieve rapid and accurate sampling in high-temperature regimes.
This paper employs a hydrodynamic framework to demonstrate that while linearized temperature correlations in a homogeneous active nematic remain unaffected by activity, spontaneous flow transitions in confined systems generate distinctive inhomogeneous temperature profiles that serve as a thermal signature of activity.
This paper demonstrates that introducing "stealthy" disorder with a vanishing power spectrum in a continuous band of wave numbers to the one-dimensional Anderson model induces effective delocalization, where the localization length scales with an arbitrarily high inverse power of the disorder strength, allowing it to exceed system sizes at fixed disorder levels.
This paper proposes a graphical model and develops both message-passing algorithms and a replica theory based on cumulant expansion to analyze and perform tensor factorization and completion of relatively high-rank tensors under sparse, random graph-based sampling in the high-dimensional dense limit.
This paper employs Koopman mode decomposition to establish a general framework that linearizes nonlinear Langevin dynamics, thereby decomposing thermodynamic dissipation into interpretable, frequency-dependent contributions from individual oscillatory modes and demonstrating how these modes govern energy loss in phenomena like coherent resonance within the noisy FitzHugh-Nagumo model.
This paper demonstrates that sudden-quench quantum Otto cycles utilizing simultaneous multi-parameter control significantly outperform single-parameter cycles in both net work and efficiency for engines, as well as in coefficient of performance for refrigerators, across experimentally realistic many-body systems like one-dimensional Bose gases and transverse-field Ising models.