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 investigates a hybrid model coupling Sachdev-Ye-Kitaev (SYK) Majorana fermions to a disordered quantum -spin bosonic system, revealing that the boson-fermion interaction stabilizes the quantum spin-glass phase with slowed dynamics while suppressing critical SYK behavior in the paramagnetic phase.
This paper introduces the FIRE-Swap first-principles framework, which utilizes machine-learning interatomic potentials to reveal that lead magnesium niobate (PMN) possesses a unique rock-salt-like chemical order and interconnected polar nanoregions within Nb clusters, providing a mesoscale explanation for its relaxor ferroelectricity that distinguishes it from PZT and PST.
This paper presents a theoretical framework based on a dipole-dipole coupled double-well potential to describe and quantify the collective buckling instability in metal-organic frameworks, specifically analyzing the phase transition and critical temperature of MOF-5 under uniaxial strain.
This paper introduces the Neural Operator Quantum State (NOQS), a foundation model that learns the solution operator mapping entire driving protocols to time-evolved quantum states, enabling efficient, single-pass predictions for both in-distribution and out-of-distribution dynamics without re-optimization.
This paper presents a universal framework and numerical optimization strategies for a measurement-based quantum thermal machine using a coupled two-level Ising system, demonstrating that such engines can achieve high efficiency and robustness against errors while being directly implementable with current quantum technologies.
This paper proposes a network-based framework that operationalizes plasticity as a structural tuning parameter defined by the ratio of system size to connectivity strength, demonstrating how this metric predicts a system's capacity for change, drives critical dynamics, and enables cross-disciplinary comparisons of adaptive efficacy.
This paper demonstrates that for a group of non-interacting diffusive searchers, an event-driven threshold resetting strategy—where the system resets whenever any searcher reaches a boundary—can significantly reduce the mean first-passage time to a target compared to reset-free dynamics, provided the population size and threshold distance are optimally tuned.
This study numerically demonstrates that while polydispersity significantly alters contact forces, local coordination, and jamming density in soft particle packings, the critical scaling of mechanical properties and the vibrational density of states remain governed solely by the distance to the jamming transition, regardless of the particle size distribution.
This paper investigates driven single-file motion with bottlenecks and reveals a hitherto unknown universality in the shapes of domain walls (shocks) that emerge under high entry/exit rates and large particle numbers, contrasting with nonuniversal shapes observed under low rates or specific parameter tuning.
Using fuzzy sphere regularization, this paper provides the first unbiased microscopic verification that the topological quantum Hall bilayer transition between the Halperin state and the Moore-Read Pfaffian is driven by a neutral fermion gap closing and is described by a 3D gauged Majorana conformal field theory.