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Related papers: Non-Gaussian PDFs from Maximum-Entropy-principle c…

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We propose a method to derive the stationary size distributions of a system, and the degree distributions of networks, using maximisation of the Gibbs-Shannon entropy. We apply this to a preferential attachment-type algorithm for systems of…

Physics and Society · Physics 2020-03-17 Cornelia Metzig , Caroline Colijn

In a recent letter, Christian Beck described a theoretical link between a family of stochastic differential equations and the probability density functions (PDF) derived from the formalism of nonextensive statistical mechanics. He applied…

Fluid Dynamics · Physics 2009-09-29 Alice M. Crawford , Nicolas Mordant , Andy M. Reynolds , Eberhard Bodenschatz

Some general considerations on the notion of entropy in physics are presented. An attempt is made to clarify the question of the differentiation between physical entropy (the Clausius-Boltzmann one) and quantities called entropies…

Statistical Mechanics · Physics 2007-05-23 Roberto Luzzi , Áurea R. Vasconcellos , J. Galvão Ramos

A simple expression for the non-equilibrium distribution function in ultra-fast transient processes is proposed. Postulating its dependence on temporal derivatives of the equilibrium integrals of motion, non-equilibrium analogues of the…

Statistical Mechanics · Physics 2025-02-18 K. S. Glavatskiy

In this paper, we consider the distribution of the supremum of non-stationary Gaussian processes, and present a new theoretical result on the asymptotic behaviour of this distribution. Unlike previously known facts in this field, our main…

Probability · Mathematics 2020-05-25 Valentin Konakov , Vladimir Panov , Vladimir Piterbarg

The Euler and Navier-Stokes fluid mechanics equations are derived using a modified statistical mechanical approach using theory taken from the Chapman-Enskog perturbation analysis used to support the lattice Boltzmann method. Additional…

Fluid Dynamics · Physics 2021-07-06 Charles Cook

Depending on context, the term entropy is used for a thermodynamic quantity, a~measure of available choice, a quantity to measure information, or, in the context of statistical inference, a maximum configuration predictor. For systems in…

Statistical Mechanics · Physics 2018-11-14 Rudolf Hanel , Stefan Thurner

In the last ten years, a number of ``Conventional Fluctuation Theorems'' have been derived for systems with deterministic or stochastic dynamics, in a transient or in a non-equilibrium stationary state. These theorems gave explicit…

Statistical Mechanics · Physics 2007-05-23 R. van Zon , E. G. D. Cohen

Statistical thermodynamics is valuable as a conceptual structure that shapes our thinking about equilibrium thermodynamic states. A cloud of unresolved questions surrounding the foundations of the theory could lead an impartial observer to…

Statistical Mechanics · Physics 2025-10-31 O. B. Ericok , J. K. Mason

It is argued that a Gibbsian formula for the space-time distribution of microscopic trajectories of a nonequilibrium system provides a unifying framework for recent results on the fluctuations of the entropy production. The variable entropy…

Statistical Mechanics · Physics 2007-05-23 C. Maes

I present an unbiased method of mapping particles to distribution functions and vice versa. This method alone defines the canonical formulation of statistical mechanics, since it can be used to derive the principle of maximum entropy in…

Astrophysics of Galaxies · Physics 2026-03-06 Jun Yan Lau

We propose a simple phenomenological modification, a Gaussian screening, of the probability distribution function which was obtained by Beck to explain experimentally measured distribution from fully developed fluid turbulence, within the…

Condensed Matter · Physics 2007-05-23 A. K. Aringazin , M. I. Mazhitov

Distribution functions of many static transport equations are found using the Maximum Entropy Principle. The equations of constraint which contain the relevant dynamical information are simply the low-lying moments of the distributions.…

Statistical Mechanics · Physics 2020-04-22 J. A. Secrest , J. M. Conroy , H. G. Miller

Turbulence is essential for understanding the structure and dynamics of molecular clouds and star-forming regions. There is a need for adequate tools to describe and characterize the properties of turbulent flows. One-point probability…

Astrophysics · Physics 2008-11-26 Ralf S. Klessen

I show that the maximum entropy principle can be replaced by a more natural assumption, that there exists a phenomenological function of entropy consistent with the microscopic model. The requirement of existence provides then a unique…

Classical Physics · Physics 2014-07-22 Łukasz Rudnicki

Inpired by recent measurements of the velocity and acceleration statistics of Lagrangian tracer particles embedded in a turbulent quantum liquid we propose a new superstatistical model for the dynamics of tracer particles in quantum…

Statistical Mechanics · Physics 2015-06-22 Shihan Miah , Christian Beck

We develop a maximum relative entropy formalism to generate optimal approximations to probability distributions. The central results consist in (a) justifying the use of relative entropy as the uniquely natural criterion to select a…

Statistical Mechanics · Physics 2008-10-17 Chih-Yuan Tseng , Ariel Caticha

The question of deriving general force/flux relationships that apply out of the linear response regime is a central topic of theories for nonequilibrium statistical mechanics. This work applies an information theory perspective to compute…

Statistical Mechanics · Physics 2019-02-04 David M. Rogers

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

The maximum entropy principle advocates to evaluate events' probabilities using a distribution that maximizes entropy among those that satisfy certain expectations' constraints. Such principle can be generalized for arbitrary decision…

Machine Learning · Statistics 2021-12-16 Santiago Mazuelas , Yuan Shen , Aritz Pérez
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