1592 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 the computable information density (CID) as a universal, data compression-based metric that instantaneously quantifies configurational entropy across diverse molecular systems without requiring prior knowledge of structural features, thereby enabling entropy-driven materials design.
This Letter derives a finite-time thermodynamic uncertainty relation for open quantum systems under Markovian feedback control, demonstrating how information-based control suppresses current fluctuations and enhances precision by linking entropy production with quantum mutual information.
This paper demonstrates that in information-limited navigation, organisms maximize up-gradient speed by adopting discrete turn strategies rather than gradual steering, with the optimal strategy shifting from simple reversals to complex, multi-angle reorientations as sensory information availability increases.
This paper derives explicit expressions for the Navier-Stokes transport coefficients of a confined quasi-two-dimensional granular gas of inelastic hard spheres at moderate densities by extending the Enskog kinetic theory via the Chapman-Enskog method and Sonine polynomial expansion.
This paper demonstrates that subjecting thin spherical shells to active fluctuations reliably induces a crumpled phase, characterized by a universal master curve for volume reduction, a general expression for the critical onset force, and a varying size exponent.
This paper presents an accessible derivation of the Poisson brackets and equations of motion for the classical Heisenberg model using only elementary algebraic concepts and the geometry of the two-sphere, making the subject suitable for advanced undergraduate students without prior knowledge of differential geometry.
This paper investigates the universal features of measurement-and-feedback control in quantum chaotic systems using the quantum Arnold cat map and an inverted harmonic oscillator model, revealing that the control transition is governed by uncertainty-limited quantum fluctuations rather than genuine quantum interference.
This paper demonstrates that stochastic position-orientation resetting can effectively overcome the transport limitations of chiral active Brownian particles by interrupting their circular motion, thereby creating a tunable dynamical landscape with distinct states that enriches search and transport capabilities beyond what is possible in achiral systems.
This paper demonstrates that in periodically forced mean-field Ginzburg-Landau models, the correct conjugate field at the critical period is the even-Fourier component of the applied field, which governs a universal order parameter scaling of and reveals a distinct parity-dependent scaling rule for mode-resolved deviations.
This paper develops and validates a diffusion approximation for systems subject to frequent, small-amplitude random resetting, demonstrating its utility in calculating stationary distributions, mean first-passage times, and characterizing dynamically induced correlations, cycles, and patterns in both single and multi-particle systems.