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 proposes learning the underlying Markov random field structure to determine optimal variable orderings for autoregressive Ising models, thereby reducing conditional complexity and improving sample fidelity compared to naive orderings.
This paper introduces a novel surrogate model that simultaneously preserves both the empirical symbol frequency distributions (such as Zipf's law) and the long-range correlation structures of symbolic sequences like language and DNA by mapping fractional Gaussian noise onto the original histogram, thereby enabling the disentanglement of structural features and the testing of scaling law origins.
This paper presents a third-order expansion of the Wigner-Kirkwood commutation function approximated via a diagonal position-space method to enable Metropolis Monte Carlo simulations of liquid Lennard-Jones He below 10 K.
This paper demonstrates that the low-temperature ferromagnet-to-paramagnet transition in the two-dimensional random-bond Ising model is controlled by a zero-temperature fixed point that can be understood via a renormalization group mapping to a noninteracting quantum problem exhibiting an infinite randomness fixed point, where the tunneling exponent equals the spin stiffness exponent.
This paper proposes a new local decoder for the toric code called the 2D signal-rule, which uses binary signal exchanges to attract defects and achieves a high pseudo-threshold with optimal scaling, offering a promising path toward practical two-dimensional local quantum memory.
This paper investigates entanglement asymmetry in fragmented quantum systems, demonstrating that while typical asymmetry is bounded in conventional settings, it can scale extensively in fragmented systems, thereby providing a distinct probe to differentiate between classical and genuine quantum fragmentation.
This paper demonstrates through analytical modeling that temporal and spatial environmental fluctuations alone are sufficient to generate substantial variability in species abundance across locations, revealing a noise-induced transition to bimodal inequality and highlighting the evolutionary advantage of finite migration rates in correlated fluctuating environments.
This study investigates how collective chemotaxis influences motility-induced phase separation in active matter, revealing that it can either suppress phase separation or generate novel dynamic patterns like traveling waves and spirals through four distinct bifurcation types, while providing analytical models that quantitatively agree with numerical simulations.
This paper demonstrates that symmetry-twisted partition functions computed via the tensor renormalization group framework effectively detect spontaneous symmetry breaking in three-dimensional models, determine the BKT transition in two dimensions, and successfully identify phase transitions in generalized two-dimensional models.
This study demonstrates that ideal Rouse polymers in time-dependent nonequilibrium baths exhibit length- and topology-dependent directed transport, where long chains and ring or star structures drift with the wave while shorter or fully connected structures drift against it.