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 derives the generic scaling forms of single-time and two-time correlators in non-equilibrium phase-ordering kinetics with dynamic exponent by establishing a new non-equilibrium representation of the Schrödinger algebra and utilizing the covariance of four-point response functions.
This paper establishes that the mixing time of open quantum systems is determined not only by the Liouvillian gap but also by the trace-norm factors of decaying eigenmodes, providing universal predictors and sparsity-based conditions for rapid mixing across strong and weak dissipation regimes to guide efficient experimental state preparation.
This paper introduces topological and geometrical fields of dislocation, disclination, and incompatibility densities to unify the description of plasticity in both crystalline and amorphous solids, demonstrating their strong predictive power for plastic events in disordered materials while uniquely disentangling rotational and translational contributions.
By incorporating strong anisotropy into a dynamical renormalization group analysis, this study identifies a new stable Gaussian fixed point for the model under steady shear flow, revealing that shear flow stabilizes long-range order in two dimensions and alters the upper critical dimensions for both conserved and non-conserved order parameters, thereby violating the equilibrium Hohenberg-Mermin-Wagner theorem.
By analyzing high-resolution data from 142 cities worldwide, this study demonstrates that intra-urban climate fluctuations in temperature and air pollution follow universal scaling functions determined by average street network properties, thereby overcoming the limitations of traditional city-size metrics and enabling more accurate reduced-complexity models for urban planning.
By modeling information scrambling in closed quantum systems as an effective open-system decoherence process, this paper derives and numerically validates a universal quantum speed limit for the out-of-time ordered correlator (OTOC) that bounds the scrambling rate based on system-environment coupling and environmental correlations.
This paper demonstrates that postselecting against exponentially unlikely error syndromes in topological stabilizer codes, such as the toric code, can suppress logical error rates from to (with ), thereby providing a scalable accuracy gain driven by the statistical rarity of failure-inducing syndrome patterns.
This paper demonstrates that quantum Otto engines utilizing nonlinear Gross-Pitaevskii qubits significantly outperform their linear counterparts in both efficiency and power, offering a new design paradigm for achieving genuine quantum thermodynamic advantage through effective many-body correlations.
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.
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.