1536 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 a new "Constraint-Modulated Viscosity Law" based on the Continuous Present Actualization premise, which outperforms standard models like VFT and MYEGA in fitting broad-window glass-forming systems by accounting for the continuous narrowing of configurational access as liquids cool.
Using high-precision tensor network methods to explicitly encode ice rules and verify the normality of the transfer operator, this study provides rigorous numerical evidence that the residual entropies of hexagonal and cubic ices are equal.
This paper investigates the fundamental limits of extracting initial qubit state information from sequential weak measurement records by analyzing mutual information across two realistic models, deriving optimal measurement durations and efficiency bounds that account for intrinsic dynamics to guide quantum device optimization and machine learning-based readout in NISQ regimes.
This paper demonstrates that topology and anomalies associated with average symmetries can predict distinct, slow-decaying critical correlations in quantum systems with strong quenched randomness, a framework successfully applied to reveal overlooked universal properties in random-singlet spin chains and disordered free-fermion states.
This paper characterizes equilibrium measures for higher-dimensional rotationally symmetric Riesz gases by establishing a converse construction that links prescribed power-series densities to their associated external potentials, utilizing hypergeometric identities to derive explicit solutions for various confining fields and applying the framework to Coulomb gases in half-spaces.
This paper proposes that for driven-dissipative quantum many-body systems with hidden time-reversal symmetry, the exponentially long metastable timescales near dissipative first-order phase transitions can be analytically predicted using a special purification of the non-equilibrium steady state, a conjecture validated through detailed studies of specific spin and cavity models where traditional semiclassical methods fail.
This paper establishes the universality of the Random Energy Model for a linear random energy system with i.i.d. real random variables and Ising spins under exponential thinning, proving that the energy levels converge to a Poisson point process while the Gibbs weights converge to a Poisson–Dirichlet law and the free energy exhibits a freezing transition.
This paper proves that operator growth in the disordered Ising chain with strictly positive couplings and fields exhibits almost factorial scaling in both time and spatial support, thereby rigorously ruling out dynamical localization at any disorder strength and revealing a structural path-entropy obstruction to perturbative many-body localization.
This paper introduces an agent-guided multi-fidelity learning framework that employs a structural agent to diagnose numerical instabilities in GW-Bethe-Salpeter calculations and applies machine learning corrections to accurately predict quasiparticle and excitonic properties in strained MoS2-WS2 bilayers, demonstrating that explicit detection of numerical fragility is essential for reliable surrogate modeling of excited-state materials.
This paper demonstrates that metastable phases, typically suppressed in equilibrium, can be tracked and characterized as regions in the complex plane of thermal fields delineated by Lee-Yang zeros, offering a new framework for understanding and engineering non-equilibrium collective states in periodically driven systems.