2407 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 establishes a direct relationship between the non-stabilizing power of generic quantum circuits and their constituent non-Clifford gates, demonstrating how random Clifford operations drive the thermalization of non-stabilizerness to its Haar-averaged value and elucidating its critical role in the emergence of quantum chaos.
This paper derives a first-principles quantum master equation for weakly coupled open many-body systems that avoids the rotating wave approximation, ensures convergence to the Gibbs state via KMS detailed balance, and offers an exponentially improved error bound and efficient quantum simulability compared to previous models.
This paper analyzes the non-equilibrium dynamics of the Ising model in one and two dimensions using a virtual walk approach associated with spin states and local energy, demonstrating that finite-time scaling of these walks yields critical exponents consistent with known theoretical values and reveals a distinct non-equilibrium region and time-dependent critical point.
This paper derives a new determinant formula for the partition function of the modified rational six-vertex model on a rectangular lattice, enabling the calculation of its homogeneous limit and the determination of the first-order free energy with boundary effects in the thermodynamic limit.
This paper presents a unified exact solution to the relativistic Boltzmann equation for a boost-invariant conformal gas on across all constant-curvature slicings, which reproduces known Bjorken and Gubser flows while introducing a novel analytic "Grozdanov flow" for hyperbolic foliations that naturally encompasses both hydrodynamic and free-streaming regimes.
This review article surveys phenomenological and microscopic models used to describe the complex, non-Arrhenius temperature responses of biological systems across various scales, defining key operational metrics like optimal temperatures and thermal limits while setting the stage for a subsequent discussion on how system-level curves emerge from interacting reactions.
This paper presents and validates a generalized algorithm for efficient Monte-Carlo sampling of metastable systems using non-local updates in collective-variable space under underdamped Langevin dynamics, demonstrating substantial performance improvements over previous overdamped approaches and extending the applicability of machine-learning-based samplers to more realistic molecular systems.
This paper reviews deterministic and stochastic network-level models to explain how Arrhenius-like temperature dependencies in individual biochemical reactions transform into complex emergent system behaviors, such as non-Arrhenius scaling and thermal limits, thereby bridging empirical temperature response curves with the molecular organization of biological systems.
This paper demonstrates that the Transient Time Correlation Function (TTCF) method is a computationally efficient and precise alternative to traditional time-averaging approaches for calculating nonequilibrium transport coefficients in both linear and nonlinear regimes, as validated through case studies of the Lorentz gas and anharmonic oscillator chains.
This paper proposes and validates a method for studying scaling dimensions of three-dimensional conformal field theories using near-term quantum simulators, demonstrating high accuracy with as few as 20 qubits on the Ising model to solve a problem that is currently difficult for classical computers.