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Shannon and Khinchin showed that assuming four information theoretic axioms the entropy must be of Boltzmann-Gibbs type, $S=-\sum_i p_i \log p_i$. Here we note that in physical systems one of these axioms may be violated. For non-ergodic…

Statistical Mechanics · Physics 2015-03-19 Stefan Thurner , Rudolf Hanel

The issue of the Gibbs paradox is that when considering mixing of two gases within classical thermodynamics, the entropy of mixing appears to be a discontinuous function of the difference between the gases: it is finite for whatever small…

Quantum Physics · Physics 2009-11-11 A. E. Allahverdyan , Th. M. Nieuwenhuizen

This paper connects two methods for finding the functional of entropy in F(R)-Gravity: Padmanabhan's and Hammad's. The resulting approach is simple to follow and yields entropy functional, which can be separated into two parts. The part…

General Relativity and Quantum Cosmology · Physics 2024-11-15 Bohuslav Matouš

The main aim of this paper is to detect dynamical properties of the Gy\"orgyi-Field model of the Belousov-Zhabotinsky chemical reaction. The corresponding three-variable model given as a set of nonlinear ordinary differential equations…

Chaotic Dynamics · Physics 2020-05-08 Judita Nagyová , Branislav Jansík , Marek Lampart

I give a brief overview of the resolution of the apparent problem of reconciling time symmetric microscopic dynamic with time asymmetric equations describing the evolution of macroscopic variables. I then show how the large deviation…

Mathematical Physics · Physics 2011-12-08 Joel L. Lebowitz

We study the behaviour of various Lyapunov functionals (relative entropies) along the solutions of a family of nonlinear drift-diffusion-reaction equations coming from statistical mechanics and population dynamics. These equations can be…

Functional Analysis · Mathematics 2019-04-09 Stanislav Kondratyev , Dmitry Vorotnikov

In this paper, we develop a method to generate the Lyapunov function for stability analysis for chemical reaction networks. Based on the Chemical Master Equation, we derive the Lyapunov Function partial differential equations (PDEs), whose…

Dynamical Systems · Mathematics 2020-10-01 Zhou Fang , Chuanhou Gao

We explore a possible application of the additive generalization of the Boltzmann-Gibbs-Shannon entropy proposed in [A.N. Gorban, I.V. Karlin, Phys. Rev. E, 67:016104 (2003)] to fully developed turbulence. The predicted probability…

Fluid Dynamics · Physics 2007-05-23 Patrick Ilg , Iliya V. Karlin , Alexander N. Gorban

The modern thermodynamics of discrete systems is based on graph theory, which provides both algebraic methods to define observables and a geometric intuition of their meaning and role. However, because chemical reactions are usually…

Statistical Mechanics · Physics 2023-04-04 Sara Dal Cengio , Vivien Lecomte , Matteo Polettini

General relationship between mean Boltzmann entropy and Gibbs entropy is established. It is found that their difference is equal to fluctuation entropy, which is a Gibbs-like entropy of macroscopic quantities. The ratio of the fluctuation…

Statistical Mechanics · Physics 2018-04-19 Pasko Zupanovic , Domagoj Kuic

The non-relativistic current algebra approach is analyzed subject to its application to studying the distribution functions of many-particle systems at the temperature equilibrium and their stability properties. We show that the classical…

Statistical Mechanics · Physics 2013-07-16 N. N. Bogolubov , A. K. Prykarpatsky

We discuss the form of the entropy for classical hamiltonian systems with long-range interaction using the Vlasov equation which describes the dynamics of a $N$-particle in the limit $N\to\infty$. The stationary states of the hamiltonian…

Statistical Mechanics · Physics 2007-05-23 T. M. Rocha Filho , A. Figueiredo , M. A. Amato

A powerful tool for studying long-term convergence of a Markov process to its stationary distribution is a Lyapunov function. In some sense, this is a substitute for eigenfunctions. For a stochastically ordered Markov process on the…

Probability · Mathematics 2021-03-01 Andrey Sarantsev

We generalize the usual exponential Boltzmann factor to any reasonable and potentially observable distribution function, $B(E)$. By defining generalized logarithms $\Lambda$ as inverses of these distribution functions, we are led to a…

Statistical Mechanics · Physics 2007-05-23 Rudolf Hanel , Stefan Thurner

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory,…

Machine Learning · Statistics 2025-03-06 Salomé A. Sepúveda Fontaine , José M. Amigó

Graph Neural Networks (GNNs) are highly vulnerable to adversarial perturbations in both topology and features, making the learning of robust representations a critical challenge. In this work, we bridge GNNs with control theory to introduce…

Machine Learning · Computer Science 2026-03-16 Haoyu Chu , Xiaotong Chen , Wei Zhou , Wenjun Cui , Kai Zhao , Shikui Wei , Qiyu Kang

The limits of scaled relative entropies between probability distributions associated with N-particle weakly interacting Markov processes are considered. The convergence of such scaled relative entropies is established in various settings.…

Probability · Mathematics 2015-02-16 Amarjit Budhiraja , Paul Dupuis , Markus Fischer , Kavita Ramanan

We build a rigorous nonequilibrium thermodynamic description for open chemical reaction networks of elementary reactions. Their dynamics is described by deterministic rate equations satisfying mass action law. Our most general framework…

Statistical Mechanics · Physics 2017-01-13 Riccardo Rao , Massimiliano Esposito

In this paper, we propose a novel technique, referred to as the Lyapunov Function PDEs technique, to diagnose persistence of chemical reaction networks with mass-action kinetics. The technique allows that every network is attached to a…

Dynamical Systems · Mathematics 2019-02-01 Xiaoyu Zhang , Zhou Fang , Chuanhou Gao

Despite their spectacular progress, language models still struggle on complex reasoning tasks, such as advanced mathematics. We consider a long-standing open problem in mathematics: discovering a Lyapunov function that ensures the global…

Machine Learning · Computer Science 2024-10-14 Alberto Alfarano , François Charton , Amaury Hayat