2392 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 investigates a power-law decaying quadratic SYK model to demonstrate how single-particle spectral transitions propagate to the many-body regime, revealing that the spectral form factor remains robust under reduced interaction ranges before perturbation theory breaks down and new spectral features emerge.
This paper establishes a general theory proving that Turing instability can emerge on adaptive symmetric networks with positive weights, demonstrating how the interplay between node dynamics and evolving link weights drives the formation of diverse spatio-temporal patterns in systems modeled by the Brusselator and FitzHugh-Nagumo equations.
This paper introduces a general and computationally tractable method using Dyson maps to restore monotonic entropy growth in non-Hermitian Markov processes with broken detailed balance, thereby enabling the application of standard statistical physics tools and inference techniques to a broad class of non-equilibrium systems.
This paper investigates the role of percolation in dropout-based neural network training, demonstrating that random connection removal can sever input-output paths and cause training breakdown, particularly in networks without biases.
This paper analytically characterizes a Hopfield model with an unlearning mechanism in the high-temperature, extensive storage limit using the replica method, demonstrating that suppressing spurious memories through unlearning enhances memory capacity and aligns with both previous theoretical findings and numerical simulations.
This paper introduces Multi-Scale Path Divergence (MSPD), a renormalization-group-inspired scalar metric that quantifies temporal multiscale heterogeneity to both guide open-ended evolution in artificial life systems and provide a principled, interpretable bridge to physical theories of complexity, outperforming black-box neural network approaches across diverse substrates.
This paper establishes a fundamental connection between quantum error correction and mesoscopic physics by demonstrating that the statistical properties of post-measurement logical states in surface codes under uniform Pauli- rotations are isomorphic to chaotic scattering matrices in quantum dots, thereby revealing a universal random-matrix ensemble governed by Altland-Zirnbauer symmetry classes.
This paper provides a constructive derivation of the continuum height field theory for the two-dimensional classical dimer model on square and honeycomb lattices by starting from an exact Grassmann integral representation, taking the continuum limit to obtain massless Dirac fermions, and applying bosonization to map the system to a height model that fully describes its long-distance correlations and topological properties.
This paper introduces a helical generalization of the Sachdev-Ye-Kitaev model in 1+1 dimensions, demonstrating that while its full interaction space breaks exact solvability, the theory flows to a free and integrable fixed point in the infrared limit due to the marginal irrelevance of all interactions.
This paper utilizes thermal inversion formulas to derive accurate asymptotic expressions for spectral densities and OPE coefficients of heavy operators in a 3D CFT dual to an interacting scalar field in AdS, demonstrating that these analytic results remain quantitatively reliable even at intermediate conformal weights despite bulk interactions.