1581 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 proposes a "nonintrinsic sector" of Landau theory where externally written microscale fields survive coarse graining to become spatially prescribed coefficients in the free-energy functional, a phenomenon realized in ion-patterned FeRh under specific correlation and frustration length hierarchies.
Through extensive molecular dynamics simulations with particles, this paper demonstrates that linear stability analysis of the Vlasov equation fails to predict the true nature and location of phase transitions in a generalized Hamiltonian Mean Field model, revealing instead that the actual paramagnetic-to-ferromagnetic transition is discontinuous and occurs at significantly higher coupling strengths than the instability thresholds identified by previous bifurcation analysis.
This paper introduces "feedback percolation," a unified framework that dynamically couples microscopic activation probabilities to the macroscopic size of the giant component, revealing a rich spectrum of complex behaviors—including explosive transitions, oscillations, and chaos—that are absent in traditional static percolation theory.
This paper demonstrates through experiments and modeling that symmetric CoFeB/Ru/CoFeB synthetic antiferromagnets in a scissors state exhibit strong frequency non-reciprocity in their acoustical spin waves, enabling unidirectional energy transfer for wavevectors parallel to the applied magnetic field.
This paper demonstrates that the derivative expansion of the Functional Renormalization Group can accurately capture the long-distance physics near the lower critical dimension of the Ising-like theory by revealing a nonuniform convergence of the fixed-point potential characterized by a boundary layer, thereby yielding analytical predictions for the lower critical dimension and critical temperature that align well with known results.
This study investigates the coupling between surface acoustic waves and ferromagnetic resonance in a CoFeB film on a LiNbO3 substrate, revealing an unexpected 2-fold symmetry in SAW energy absorption that is attributed to weak in-plane uniaxial anisotropy rather than dipolar interactions.
This paper demonstrates that underdamped autonomous heat engines can robustly violate thermodynamic uncertainty relations by exploiting resonant coupling to suppress current fluctuations, offering new design principles for efficient microscopic engines and clocks.
This paper proposes and validates via Monte Carlo simulations a novel protocol that directly reconstructs the relativistic inverse-temperature four-vector from electromagnetic fluctuation correlations in a drifting medium, offering the first experimental method to resolve the century-old controversy regarding the transformation properties of relativistic thermal states without relying on external probes or absolute calibration.
This paper demonstrates that the dynamic relaxation of magnetization and magnetic monopole density in classical spin ice following a field quench near the Kasteleyn transition is accurately described by a solvable stochastic model of independent, growing strings of flipped spins, which successfully captures critical scaling behavior and explains the breakdown of this picture at higher monopole densities.
This paper derives a level-2.5 large deviation principle for self-interacting jump processes using an exponential tilting construction that reveals a time-scale separation between microscopic dynamics and memory-driven rate evolution, thereby enabling the extension of kinetic and thermodynamic uncertainty relations to non-Markovian systems.