1593 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 utilizes analytic bootstrap methods to define and characterize diagonal boundaries in critical loop models via a complex parameter, deriving explicit formulas for disc correlation functions and demonstrating that specific parameter values yield discrete spectra of degenerate representations, while also providing a lattice interpretation where loops cannot terminate or change weight upon touching such boundaries.
This paper demonstrates that utilizing the special conformal generator within the fuzzy sphere framework to identify Ising CFT primary states—distinguished by an gap from descendants—enables more accurate extrapolation of OPE coefficients to the continuum limit compared to previous methods.
This paper establishes non-perturbative and perturbative stability constraints on nonequilibrium renormalization group flows by demonstrating that conditional mutual information serves as a monotonic scaling function and provides bounds for symmetry-breaking states under quantum channels.
This paper reveals that introducing vacancies into a coupled driven system weakens reverse bias, thereby enabling novel ordered phases—specifically finite current with partial phase separation (FPPS) and vacancy induced phase separation (VIPS)—where long-range order emerges even when aligned bias is weaker than reverse bias.
This paper proposes a fine-grained parallel tensor network design utilizing FPGAs and a quad-tile partitioning strategy to drastically reduce the computational cost scaling of iTEBD and HOTRG algorithms from to and from to , respectively, thereby offering a scalable hardware solution for large-scale quantum many-body calculations.
This paper demonstrates that spontaneous parity breaking serves as a systematic guiding principle for predicting and rationalizing the emergence of nontrivial phases, such as intermediate-spin parity-broken states and bilayer supersolids, in frustrated quantum antiferromagnets on triangular lattices, a conclusion validated by large-scale tensor network calculations.
This paper utilizes time-resolved geometric analysis of bacterial colony growth to demonstrate that visually distinct morphologies can emerge within a single-scale growth regime, with deviations from compact scaling reflecting intrinsic dynamical boundary reorganization rather than growth arrest.
This paper presents a polymer self-consistent field theory for atoms using Gaussian basis functions and an excluded-volume model to enforce the Pauli-exclusion principle, successfully calculating binding energies and electron densities for elements from hydrogen to krypton while recovering standard quantum mechanical limits.
This paper extends the universality of quantum thermalization by demonstrating that the subsystem thermalization hypothesis holds generically for small subsystems in quantum spin chains with various symmetries, not only for standard thermal ensembles but also for generalized and partial Generalized Gibbs Ensembles (p-GGEs) that incorporate partial sets of conserved charges.
This paper presents numerical simulations and explicit gate count analyses using Qrisp to characterize the behavior of the Double-bracket Quantum Imaginary-Time Evolution (DB-QITE) algorithm, specifically focusing on its signatures when navigating saddle points in the Riemannian steepest-descent energy landscape.