2392 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 how the work required to insert a particle into an active fluid depends on activity, density, and protocol, revealing that while average work decreases with activity and remains protocol-dependent, its fluctuations exhibit non-Gaussian tails and show opposing trends compared to steady-state densities observed in diffusive contact.
This paper introduces an "information blueprint" algorithm inspired by renormalization-group techniques to identify condition-dependent transcription factor binding sites in non-coding genomic regions by compressing global sequence information into collective coordinates, a method validated on *E. coli* data to reveal novel regulatory elements across various growth conditions.
This paper investigates two-banded, non-Hermitian random matrices inspired by sparse neural networks, revealing how the competition between random sign disorder and directional bias drives distinct delocalization transitions and creates complex spectral structures, including loops of extended states and specific eigenvalue degeneracies, in both SSH chain and ladder models.
This paper analytically characterizes how different hidden unit activation functions in Restricted Boltzmann Machines influence the statistics of induced interactions and the ability to learn complex, higher-order data structures, demonstrating that rapidly increasing nonlinearities like the Exponential function can significantly facilitate the representation and learning of such patterns.
This paper derives thermodynamic lower bounds for the energy costs of exact and stochastic gradient descent-based simple linear regression, using these bounds to establish energy-aware scaling laws for optimal dataset sizes and methods to lower bound entropy production from algorithmic mismatches.
This paper elucidates the emergence of Kardar-Parisi-Zhang superdiffusion in the PXP model by demonstrating that finite-temperature energy transport bridges short-time coherent magnon dynamics and long-time hydrodynamics through a crossover governed by an activated damping time.
This paper demonstrates that the requirement for a quantum system to remain describable by classical hydrodynamics at low temperatures necessitates a finite classical region within the light cone, which in turn forces the effective relaxation rate to be at least Planckian, thereby deriving Planckian scaling of transport coefficients as a consequence of hydrodynamic self-consistency rather than microscopic quantum constraints.
This paper demonstrates that introducing diffusing diffusivity into the Bouchaud-Mézard model of random growth with redistribution leads to a stationary Pareto wealth tail whose exponent is determined by the interplay between high-diffusivity states and redistribution rates, rather than simply by the mean diffusivity.
This study demonstrates that dielectric spectroscopy can non-destructively track the coupled dynamics of granular temperature and configurational entropy in graphite powders, revealing that their structural relaxation follows an Adam-Gibbs-like relationship analogous to that observed in glass-forming liquids.
This paper utilizes the Schwinger-Keldysh formalism to derive quantum corrections to semiclassical Langevin dynamics for dissipative systems, demonstrating that these corrections are governed by zero-point energy in the low-temperature, weak-damping regime and applying the results to Josephson and bosonic junctions where they reach significant percent-level magnitudes.