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Entropy production is a universal measure of irreversibility and energy dissipation in physical, chemical, and biological systems operating far from equilibrium. However, quantifying and spatiotemporally localising it in complex processes…

Statistical Mechanics · Physics 2026-05-18 Biswajit Das , Sreekanth K Manikandan

Entropy production is the crucial quantity characterizing irreversible phenomena and the second law of thermodynamics. Yet, a ubiquitous definition eludes consensus. Given that entropy production arises from incomplete access to…

Quantum Physics · Physics 2024-08-26 Adalberto D. Varizi , Pedro S. Correia

We propose a stochastic dynamics to be associated to a deterministic motion defined by a set of first order differential equation. The transitions that defined the stochastic dynamics are unidirectional and the rates are equal to the…

Statistical Mechanics · Physics 2024-11-13 Mário J. de Oliveira

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

The Tsallis entropy and Fisher information entropy (matrix) are very important quantities expressing information measures in nonextensive systems. Stationary and dynamical properties of the information entropies have been investigated in…

Statistical Mechanics · Physics 2009-11-13 Hideo Hasegawa

Entropy production characterizes irreversibility. This viewpoint allows us to consider the thermodynamic uncertainty relation, which states that a higher precision can be achieved at the cost of higher entropy production, as a relation…

Statistical Mechanics · Physics 2021-12-09 Yoshihiko Hasegawa

Let $X$ be a discrete random variable with support $S$ and $f : S \to S^\prime$ be a bijection. Then it is well-known that the entropy of $X$ is the same as the entropy of $f(X)$. This entropy preservation property has been well-utilized to…

Information Theory · Computer Science 2007-07-13 Chandra Nair , Balaji Prabhakar , Devavrat Shah

Entropic dynamics, a program that aims at deriving the laws of physics from standard probabilistic and entropic rules for processing information, is developed further. We calculate the probability for an arbitrary path followed by a system…

Classical Physics · Physics 2016-09-08 Ariel Caticha

Fluctuation theorems make use of time reversal to make predictions about entropy production in many-body systems far from thermal equilibrium. Here we review the wide variety of distinct, but interconnected, relations that have been derived…

Statistical Mechanics · Physics 2007-08-02 R. J. Harris , G. M. Schütz

Inequalities between transportation costs and Fisher information are known to characterize certain concentration properties of Markov processes around their invariant measures. This note provides a new characterization of the quadratic…

Probability · Mathematics 2020-12-07 Daniel Lacker , Lane Chun Yeung

Exploiting previous results on Markovian dynamics and fluctuation theorems, we study the consequences of memory effects on single realizations of nonequilibrium processes within an open system approach. The entropy production along single…

Statistical Mechanics · Physics 2015-06-12 Bruno Leggio , Anna Napoli , Heinz-Peter Breuer , Antonino Messina

The entropy rates of the Wright-Fisher process, the Moran process, and generalizations are computed and used to compare these processes and their dependence on standard evolutionary parameters. Entropy rates are measures of the variation…

Dynamical Systems · Mathematics 2014-03-26 Marc Harper

Entropic Dynamics is a framework in which dynamical laws such as those that arise in physics are derived as an application of entropic methods of inference. No underlying action principle is postulated. Instead, the dynamics is driven by…

Quantum Physics · Physics 2018-02-23 Ariel Caticha

We introduce and analyze a model for the transport of particles or energy in extended lattice systems. The dynamics of the model acts on a discrete phase space at discrete times but has nonetheless some of the characteristic properties of…

Mathematical Physics · Physics 2015-06-12 Raphael Lefevere

Random fields are useful mathematical objects in the characterization of non-deterministic complex systems. A fundamental issue in the evolution of dynamical systems is how intrinsic properties of such structures change in time. In this…

Information Theory · Computer Science 2017-03-14 Alexandre L. M. Levada

Entropy production characterizes the thermodynamic irreversibility and reflects the amount of heat dissipated into the environment and free energy lost in nonequilibrium systems. According to the thermodynamic uncertainty relation, we…

Statistical Mechanics · Physics 2020-05-01 Tan Van Vu , Van Tuan Vo , Yoshihiko Hasegawa

We consider the analysis of probability distributions through their associated covariance operators from reproducing kernel Hilbert spaces. We show that the von Neumann entropy and relative entropy of these operators are intimately related…

Information Theory · Computer Science 2022-08-29 Francis Bach

The information-theoretic representation of quantum systems, which complements the familiar energy description of the density-functional and wave-function-based theories, is here discussed. According to it, the internal disorder of the…

Quantum Physics · Physics 2013-05-27 J. S. Dehesa , D. Manzano , P. S. Sánchez-Moreno , R. J. Yáñez

This paper develops a rigorous probabilistic framework that extends denoising diffusion models to the setting of noncommutative random variables. Building on Voiculescu's theory of free entropy and free Fisher information, we formulate…

Probability · Mathematics 2025-11-04 Swagatam Das

Generative diffusion models have emerged as a powerful class of models in machine learning, yet a unified theoretical understanding of their operation is still developing. This paper provides an integrated perspective on generative…

Machine Learning · Statistics 2026-03-27 Dejan Stancevic , Luca Ambrogioni