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 provides a pedagogical review of using Conformal Field Theory techniques to compute Schramm-Loewner Evolution observables in the upper half-plane, successfully recovering known results like Schramm's left-passage probability and anchored cluster densities while deriving new formulas for the densities of pivotal points in critical Fortuin-Kasteleyn clusters.
This paper reveals a hierarchical entanglement structure in chaotic many-body dynamics where, following local quantum quenches, the full state exhibits a Renyi-index-tuned transition with area-law scaling for and volume-law scaling for , while the linear response is dominated by a low-dimensional Schmidt sector that itself undergoes an area-to-volume-law transition.
This paper proposes a minimal theoretical framework incorporating stochastic mass fluctuations to explain the anomalous center-of-mass diffusion scaling () observed in clusters of active Brownian particles, demonstrating that a fluctuation-driven term dominates over conventional thermal noise to reproduce simulation results.
This paper develops a general framework based on form factors to analyze the real-time dynamics of integrable boundary quantum quenches, specifically investigating the time evolution of the pre-quench vacuum in the Lee-Yang model and validating these analytical results with numerical calculations using the truncated conformal space approach.
This paper proposes enhancing the Factorization Machine with Quadratic-optimization Annealing (FMQA) algorithm by designing initial training data using Latin hypercube and Sobol' sampling methods to ensure complete marginal bit coverage in one-hot encoding, thereby improving optimization performance on integer and discretized continuous variable problems.
This paper establishes a unified frequency-domain fluctuation-response theory for nonequilibrium steady states that expresses the power spectrum of observables as a quadratic form of local responses, thereby extending static relations to finite frequencies and unifying various uncertainty and thermodynamic relations.
This work investigates the universality of kink-kink correlations in one-dimensional transverse Ising models under algebraic quenches across a quantum critical point and shows that while superlinear quenches are determined exclusively by the Kibble-Zurek length, sublinear quenches require an additional dephasing length and exhibit a continuously varying compressed exponential decay in their correlation functions.
This paper demonstrates that time-averaged observables in driven systems generically exhibit singularities in their finite-order derivatives at the onset of Hopf bifurcations due to geometric phase averaging, creating a universal hierarchy of nonanalytic behavior despite the absence of divergent stationary states.
By employing high-frequency alternating-field susceptibility measurements on DyTiO, this study corrects previous underestimations of the anomalous diffusion exponent , establishes its deviation from Brownian motion up to 20 K, and reveals its sample-dependent nature within the dense Coulomb fluid of magnetic monopoles.
This paper reveals that distinct dynamical observables in chaotic systems can share identical large deviation rate functions when their defining functions differ by a "derived" term, a property that also leads to -independent, non-Gaussian distributions for purely derived observables, thereby unifying and explaining various existing results in chaos theory.