2356 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 a minimal model and the Ad-hoc potential method to reveal two distinct microscopic pathways—population-driven accretion and coupling-driven merger—that govern the nucleation, propagation, and recovery of synchronized clusters in power grids, offering a dynamic framework for enhancing grid resilience.
This paper establishes a finite-temperature Gaussian-state framework for quantum energy teleportation in a one-dimensional harmonic chain, demonstrating that while extracted energy is exponentially screened by thermal correlation lengths at finite temperatures, it follows a distinct power-law scaling in the zero-temperature critical limit, with squeezed measurements modifying the extraction efficiency without altering the large-distance scaling behavior.
This paper employs an atomistic framework to demonstrate that interfacial orbital torques are the primary mechanism driving the efficient excitation of exchange-dominated terahertz magnons in nanoscale ferromagnets, resolving the microscopic origins of mode-selective excitation observed in recent experiments.
This paper demonstrates that chemotaxis in two-species reaction-diffusion systems can induce nonmonotonic control over pattern formation, enabling re-entrant transitions between homogeneous and patterned states, triggering novel instabilities, and driving morphological shifts between spot and stripe patterns.
This study demonstrates that chemotactic interactions in a reaction-diffusion Selkov model induce nonmonotonic and re-entrant transitions between homogeneous oscillations and stationary patterns (spots and stripes), revealing that chemotaxis acts as a critical control parameter for instability selection, wavelength tuning, and nonlinear morphological transitions.
This paper establishes a unifying framework for dynamical phase transitions in both isolated quantum and classical Brownian systems by demonstrating that, in the semiclassical and weak-noise limits, the condensation of Fisher zeros in the complex-time plane reveals a direct connection between quantum and classical dynamics where the semiclassical limit acts as the thermodynamic limit.
This paper demonstrates that prethermalization is not solely determined by the Hamiltonian's spectral hierarchy but is also selective to specific observables and initial states, while establishing that the Loschmidt echo provides a rigorous lower bound for prethermal lifetimes in unitary systems.
This paper employs an information geometric approach using natural gradients to derive and validate a novel upper bound on the reaction rates of general chemical reaction networks, demonstrating its superiority over conventional methods and highlighting its potential broader applications to hypergraph-based systems.
This paper investigates how space-dependent stochastic resetting influences the mean first passage time for diffusive particles in various potentials, demonstrating that the optimal strategy involves lower reset rates near the target and that the benefits of resetting are most pronounced when drift is weak compared to noise.
This paper demonstrates that monitored continuous-time quantum walks with two targets exhibit a nonanalytic phase transition in splitting probabilities controlled by the sampling time, where short sampling intervals yield a universal 1/2 probability independent of initial conditions, while longer intervals induce a nonuniversal, fluctuating regime.