1581 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 introduces a novel numerical bootstrap framework based on moment observables that provides rigorous bounds on conformal field theory spectra, revealing new continuous families of kinks and spectral reorganizations across dimensions that are difficult to access with traditional methods.
This paper explains the origin of unidirectional edge currents in chiral active liquids as a consequence of global angular momentum conservation, deriving an intensive Ohmic-like conductance law and a Gaussian current distribution that are validated by molecular dynamics simulations.
This study establishes that asymmetric energy landscapes in glasses drive large macroscopic diffusion activation energies through dominant back-and-forth correlated atomic motions, rather than high local rearrangement barriers, providing a quantitative framework that links atomic-scale dynamics to macroscopic transport across various disordered materials.
This paper derives analytical expressions for the mean, variance, and autocorrelation of a quasiparticle in a one-dimensional hard rod gas, revealing that long-range initial correlations induce a diffusive-scale correction to the standard Euler generalized hydrodynamic equations that depends on the specific form of those correlations.
This paper investigates noisy, stroboscopically monitored qubit systems using IBM quantum hardware and a statistical-physics model to demonstrate that while integer-quantized recurrence times are robust far from revivals, weak noise dramatically alters behavior near revivals by inverting expected dips into peaks due to a competition between measurement-driven infinite-temperature and relaxation-driven low-temperature steady states.
This paper proposes a maximum entropy principle for quantum wavefunction ensembles at thermal equilibrium, termed the Scrooge ensemble, which demonstrates that valid equilibrium states require constraining measurement entropy to equal the Rényi divergence with respect to the Gibbs state, in addition to standard energy constraints.
This paper introduces and characterizes various models of active quantum particles driven by engineered dissipation, demonstrating that despite diverse microscopic mechanisms, they universally exhibit a crossover from diffusive to active-diffusive motion and a strong sensitivity to boundary conditions via the Liouville skin effect, while also discussing their quantum fluctuations, experimental realizations, and many-body implications.
This paper extends the cross derivative of Gibbs free energy to quantum systems, demonstrating its effectiveness in identifying Gaussian-type quantum phase transitions in the spin-1 XXZ chain by revealing a logarithmically diverging valley structure that accurately yields critical points and exponents consistent with established literature.
This paper presents a hybrid classical-quantum algorithm that combines machine learning for conformational exploration with quantum annealing to efficiently generate uncorrelated transition paths, successfully simulating a millisecond-scale protein rearrangement that matches results from specialized supercomputers.
This paper introduces a random quantum circuit ensemble with time-reversal symmetry to derive a statistical mechanics model for entanglement and chaos, revealing that while standard time-reversal invariance preserves the universality class of measurement-induced phase transitions, enforcing global time-reversal invariance on individual quantum trajectories leads to novel critical exponents.