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 demonstrates that inhomogeneous polymers driven by temporally patterned active processes can achieve specific conformations and strong compaction through tension-mediated coupling of distant loci, where delayed excitations induce coherent motion and folding.
This paper employs macroscopic fluctuation theory to derive exact typical charge probability distributions for stochastic charged cellular automata, successfully capturing the anomalous fluctuations arising from the coexistence of normal and convective diffusion in these linearly degenerate systems.
This paper investigates a generalized fractional Rabi model using Caputo derivatives to demonstrate how fractional temporal nonlocality induces controllable damping and dephasing in two-level quantum systems, offering new experimental signatures and pathways for exploring memory effects in materials like graphene and topological chains.
This paper extends the framework of entanglement asymmetry to higher-form symmetries, deriving an entropic Coleman-Mermin-Wagner theorem that forbids spontaneous breaking of continuous -form symmetries in spacetime dimensions while quantifying symmetry breaking through the growth of entanglement asymmetry and the counting of Goldstone fields.
Using coarse-grained molecular dynamics simulations, this study reveals that the interplay between arrested phase separation and vitrification in hard colloid-star polymer mixtures induces a complex decoupling of single-particle and collective dynamics, characterized by population splitting and multiscale non-Gaussian behavior of the hard tracers within the soft glassy matrix.
This paper presents a neural network model that achieves temperature-dependent pattern recall by embedding distinct patterns into fully connected and sparse graphs, demonstrating through Monte-Carlo simulations that tuning relative weights induces a first-order phase transition where the system preferentially recalls the more thermally robust pattern while potentially failing to access the sparse pattern at low temperatures due to high free-energy barriers.
This paper proposes the Principle of Biological Time Equivalence (PBTE), a thermodynamic framework explaining the observed conservation of physiological cycle counts across species by demonstrating that lifetime heartbeat and breath totals are determined by the ratio of total entropy production to the mass-invariant entropy cost per cycle.
The paper introduces CluMP, a scalable optimization algorithm that leverages Belief Propagation to perform collective, frustration-tolerant cluster updates, enabling efficient navigation of complex energy landscapes in QUBO problems by bypassing local trapping more effectively than traditional single-spin heuristics.
This paper demonstrates that the tricritical point of the one-dimensional cluster O'Brien-Fendley model realizes a topologically nontrivial tricritical Ising universality class characterized by a protected twofold degeneracy and distinct boundary structures, including an exponential energy splitting that differentiates it from the ordinary Ising* critical point.
This paper establishes that the triangular plaquette model exhibits super-Arrhenius relaxation with an infinite volume relaxation time scaling between and in any dimension, thereby recovering fragile glass phenomenology without kinetic constraints and revealing a surprising dependence of finite-size relaxation on domain geometry through novel combinatorial and renormalization techniques.