1537 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 benchmarks functional-renormalization-group density functional theory (FRG-DFT) against the exact thermodynamics of the single-site Bose-Hubbard model, demonstrating that incorporating a specific self-interaction correction and using a maximum-entropy closure enables the accurate derivation of ab initio density functionals for quantum many-body systems.
This paper develops a global thermodynamic framework for liquid-gas coexistence under weak gravity and heat conduction by constructing a variational free-energy function that decomposes into an effective-gravity configurational term and a residual excess-latent-heat contribution, the latter being essential for recovering fundamental thermodynamic relations and reshaping the free-energy landscape.
The paper demonstrates that most existing velocity-independent Bhatnagar-Gross-Krook models for multispecies systems fail to satisfy the Onsager reciprocal relations, thereby complicating the calibration of their transport properties to match specific fluids.
This paper investigates the pursuit-evasion dynamics between a deterministic, self-steering pursuer and a stochastic, cognitive evader in two dimensions, revealing that the evader's capture time is significantly influenced by whether it adopts a high-risk backward maneuver or a forward-tumbling strategy with continuous adjustments depending on the pursuer's dominance.
By analyzing a massive dataset of 131,063 island topographic profiles across eight orders of magnitude, this study estimates the Hurst exponent through four distinct statistical laws to reveal how coastal erosion and sedimentation differentially influence the fractal scaling behavior of Earth's island geomorphology.
This paper presents an end-to-end framework for systematically analyzing rare but significant events in large language models, offering practical tools for their generation, probability estimation, and error analysis to address challenges arising from the models' massive scale and probabilistic nature.
This paper introduces Coarse-Grained Boltzmann Generators (CG-BGs), a framework that combines flow-based generative models with learned potentials of mean force to enable efficient, asymptotically correct equilibrium sampling of large molecular systems in reduced coarse-grained coordinate spaces.
This paper proposes a machine learning-driven method to improve lattice operators in critical systems, successfully constructing estimators with enhanced overlap to continuum conformal fields that significantly reduce finite-size corrections and yield more accurate scaling dimensions for the Ising and q=3 Potts models.
This paper reviews the concept of Yang-Baxter integrability for constrained anyonic chains, establishes the emergence of Temperley-Lieb algebras in specific cases, and extends the classification of integrable models to various fusion categories up to rank 7 using a modified boost operator formalism.
This paper numerically investigates the longest increasing subsequence (LIS) of biased Gaussian random walks, revealing that while the symmetric case exhibits a growth regime, introducing a positive drift causes the mean LIS length to transition to linear growth that increasingly aligns with the record count as the drift increases.