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We apply the stochastic thermodynamics formalism to describe the dynamics of systems of complex Langevin and Fokker-Planck equations. We provide in particular a simple and general recipe to calculate thermodynamical currents, dissipated and…

Statistical Mechanics · Physics 2019-01-30 Simone Borlenghi , Anna Delin

In this paper, we suppose a possible extension of Gibbs ensemble theory so that it can provide a reasonable description to phase transitions and spontaneous symmetry breaking. The extension is founded on three hypotheses, and can be…

Statistical Mechanics · Physics 2008-11-26 Ming-wen Xiao

A distributional route to Gaussianity, associated with the concept of Conservative Mixing Transformations in ensembles of random vector-valued variables, is proposed. This route is completely different from the additive mechanism…

Statistical Mechanics · Physics 2023-01-11 Massimiliano Giona , Chiara Pezzotti , Giuseppe Procopio

A method is proposed to approximate the unlimited subcritical set of Mayer`s reducible cluster integrals (i.e., the power coefficients of the known virial expansions for pressure and density in powers of activity) on the basis of…

Chemical Physics · Physics 2020-03-05 M. V. Ushcats , L. A. Bulavin

We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid-structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation-dissipation…

Mesoscale and Nanoscale Physics · Physics 2023-02-28 Pat Plunkett , Jon Hu , Chris Siefert , Paul J. Atzberger

In 1988, Constantino Tsallis proposed an extension of the Boltzmann statistical mechanics by postulating a new entropy formula, $S_q = k_B\ln_q W$, where $W$ is the number of microstates accessible to the system, and $\ln_q$ defines a…

Statistical Mechanics · Physics 2025-03-03 J. A. S. Lima , M. H. Benetti

We develop the argument that the Gibbs-von Neumann entropy is the appropriate statistical mechanical generalisation of the thermodynamic entropy, for macroscopic and microscopic systems, whether in thermal equilibrium or not, as a…

Quantum Physics · Physics 2008-01-23 O. J. E. Maroney

A new method to simulate probability distributions in regions where the events are VERY unlikely (e.g. p ~ 10^{-40}) is presented. The basic idea is to represent the underlying probability space by the phase space of a physical system. The…

Disordered Systems and Neural Networks · Physics 2009-11-07 Alexander K. Hartmann

Certain fluctuations in particle number at fixed total energy lead exactly to a cut-power law distribution in the one-particle energy, via the induced fluctuations in the phase-space volume ratio. The temperature parameter is expressed…

Statistical Mechanics · Physics 2014-12-10 Tamas Sandor Biro , Peter Van , Gergely Gabor Barnafoldi , Karoly Urmossy

Star clusters are studied widely both as benchmarks for stellar evolution models and in their own right. Cluster age and mass distributions within galaxies are probes of star formation histories, and of cluster formation and disruption…

Solar and Stellar Astrophysics · Physics 2015-05-18 Morgan Fouesneau , Ariane Lançon

The probability density function (PDF) of the gas density in turbulent supersonic flows is investigated with high-resolution numerical simulations. In a systematic study, we compare the density statistics of compressible turbulence driven…

Astrophysics · Physics 2009-11-13 Christoph Federrath , Ralf S. Klessen , Wolfram Schmidt

Galaxies and clusters distributions show two major properties: (i) the positions of galaxies and clusters are characterized by a power law distribution indicating properties with respect to their positions. (ii) The distribution of masses…

Astrophysics · Physics 2009-09-25 Francesco Sylos Labini , Luciano Pietronero

This article extends the non-extensive entropy of Tsallis and uses this entropy to model an energy producing system in an absorbing heat bath. This modified non-extensive entropy is superficially identical to the one proposed by Tsallis,…

Statistical Mechanics · Physics 2007-05-23 Mark Fleischer

Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples in thermodynamic equilibrium. The equilibrium distribution is usually defined…

Statistical Mechanics · Physics 2022-09-07 Manuel Dibak , Leon Klein , Andreas Krämer , Frank Noé

We introduce weak barycenters of a family of probability distributions, based on the recently developed notion of optimal weak transport of mass by Gozlanet al. (2017) and Backhoff-Veraguas et al. (2020). We provide a theoretical analysis…

Machine Learning · Statistics 2023-03-13 Elsa Cazelles , Felipe Tobar , Joaquín Fontbona

We develop here a semiparametric Gaussian mixture model (SGMM) for unsupervised learning with valuable spatial information taken into consideration. Specifically, we assume for each instance a random location. Then, conditional on this…

Methodology · Statistics 2025-10-21 Baichen Yu , Jin Liu , Hansheng Wang

Segregation by thermal diffusion of an intruder immersed in a sheared granular gas is analyzed from the (inelastic) Boltzmann equation. Segregation is induced by the presence of a temperature gradient orthogonal to the shear flow plane and…

Statistical Mechanics · Physics 2015-05-18 Vicente Garzó , Francisco Vega Reyes

The change in the angular momentum of an atomic cluster following evaporation is investigated using rigorous phase space theory and molecular dynamics simulations, with an aim at the possible rotational cooling and heating effects.…

Statistical Mechanics · Physics 2009-11-10 P. Parneix , F. Calvo

Motivated by the challenge of sampling Gibbs measures with nonconvex potentials, we study a continuum birth-death dynamics. We improve results in previous works [51,57] and provide weaker hypotheses under which the probability density of…

Analysis of PDEs · Mathematics 2024-01-15 Yulong Lu , Dejan Slepčev , Lihan Wang

We propose a method for inference in generalised linear mixed models (GLMMs) and several extensions of these models. First, we extend the GLMM by allowing the distribution of the random components to be non-Gaussian, that is, assuming an…

Methodology · Statistics 2021-07-27 Jeanett S. Pelck , Rodrigo Labouriau
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