🔬 Category

cond-mat.stat-mech

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.

Topology of the Fermi surface and universality of the metal-metal and metal-insulator transitions: dd-dimensional Hatsugai-Kohmoto model as an example

This paper advances the theory of Fermi Surface Topology (FST) transitions by analyzing the exactly solvable dd-dimensional Hatsugai-Kohmoto model to demonstrate that the FST universality class, characterized by the Euler characteristic and Lee-Yang zeros, robustly describes metal-insulator and gapless-to-gapless transitions across various interaction regimes.

Gennady Y. Chitov2026-05-20⚛️ quant-ph

Realization of fractional Fermi seas

This paper reports the experimental realization of fractional Fermi seas in an excited one-dimensional Bose gas, evidenced by Friedel oscillations, thereby confirming exotic quantum states predicted by generalized exclusion statistics and opening new avenues for quantum thermodynamics and applications.

Yi Zeng, Alvise Bastianello, Sudipta Dhar, Zekui Wang, Xudong Yu, Milena Horvath, Grigori E. Astrakharchik, Yanliang Guo, Hanns-Christoph Nägerl, Manuele Landini2026-05-20🔬 cond-mat

First-passage processes in a deterministic one-dimensional cellular automaton model of traffic flow

This paper presents analytical, closed-form expressions for the distributions of first-stopping, last-stopping, and total stopping events for individual cars in a deterministic one-dimensional cellular automaton traffic model (Rule 184), offering new insights into congestion dynamics and relaxation processes across its low- and high-density phases.

Ofer Biham, Gilad Hertzberg Rabinovich, Eytan Katzav2026-05-20🔬 cond-mat

Informational blueprints reveal condition-dependent gene regulatory architectures

This paper introduces an "information blueprint" algorithm inspired by renormalization-group techniques to identify condition-dependent transcription factor binding sites in non-coding genomic regions by compressing global sequence information into collective coordinates, a method validated on *E. coli* data to reveal novel regulatory elements across various growth conditions.

Doruk Efe Gökmen, Rosalind Wenshan Pan, Tom Röschinger, Stephen Quake, Hernan Garcia, Rob Phillips, Vincenzo Vitelli2026-05-20🧬 q-bio

Banded non-Hermitian random matrices, neural networks, and eigenvalue degeneracies

This paper investigates two-banded, non-Hermitian random matrices inspired by sparse neural networks, revealing how the competition between random sign disorder and directional bias drives distinct delocalization transitions and creates complex spectral structures, including loops of extended states and specific eigenvalue degeneracies, in both SSH chain and ladder models.

Richard Huang, David R. Nelson2026-05-20🔬 cond-mat

Activation Functions, Statistics and Learning of Higher-Order Interactions in Restricted Boltzmann Machines

This paper analytically characterizes how different hidden unit activation functions in Restricted Boltzmann Machines influence the statistics of induced interactions and the ability to learn complex, higher-order data structures, demonstrating that rapidly increasing nonlinearities like the Exponential function can significantly facilitate the representation and learning of such patterns.

Giovanni di Sarra, Yasser Roudi2026-05-20🔬 cond-mat

Planckian dissipation from classical hydrodynamics

This paper demonstrates that the requirement for a quantum system to remain describable by classical hydrodynamics at low temperatures necessitates a finite classical region within the light cone, which in turn forces the effective relaxation rate to be at least Planckian, thereby deriving Planckian scaling of transport coefficients as a consequence of hydrodynamic self-consistency rather than microscopic quantum constraints.

Laura Foini, Jorge Kurchan, Silvia Pappalardi2026-05-20⚛️ hep-th