1940 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 a periodically kicked long-range interacting Ising model exhibits robust time-translation symmetry breaking and persistent period doubling for various initial states, driven by a minority of exponentially numerous Floquet eigenstates that display quantum many-body scars, -spectral pairing, and long-range order.
This paper demonstrates that while operator growth in closed quantum systems follows deterministic Hamiltonian flow in an emergent phase space, coupling to an environment transforms this dynamics into a stochastic process where dissipation induces diffusion and ultimately destroys the hyperbolic mechanism responsible for exponential complexity growth.
This paper provides a complete characterization of the phase diagram for the Ising model on a two-community stochastic block model, detailing the almost sure uniqueness/non-uniqueness phase transition, the convergence of magnetization to specific Dirac mixtures in the supercritical regime, and the distinct fluctuation behaviors (Gaussian vs. non-Gaussian) in the subcritical and critical regions.
This paper derives exact analytical expressions for the mean first-encounter time of multiple random walkers on networks under a simultaneous resetting protocol, establishing criteria for its efficiency and revealing a trade-off between synchronization and exploration compared to independent resetting strategies.
This paper presents a direct algebraic proof demonstrating that the real parts of all eigenvalues of the Liouvillian super-operator in finite-dimensional Markovian open quantum systems are non-positive, thereby establishing system stability without relying on the indirect argument of quantum channel contractivity.
This paper presents an unsupervised machine learning framework that combines classical shadow tomography with principal component analysis to detect and classify diverse quantum phase transitions, including both symmetry-breaking and topological types, without requiring prior knowledge of the Hamiltonian or explicit order parameters.
This paper presents a multi-scale modeling framework that extends the Rouse model and introduces a new upper-convected electro-Maxwell continuum model to demonstrate that the upper-convected time derivative of the electric field dyadic is essential for accurately capturing the quadratic scaling of viscosity in charged polymers under combined flow and electric fields, a finding validated by coarse-grained molecular dynamics simulations.
This paper investigates the impact of two-way coupling in two-dimensional dusty turbulence, revealing enhanced intermittency and modified spectral scaling that are effectively captured by a proposed multiscale forcing framework modeling particle feedback as localized small-scale forcing.