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In a first order theory of dissipative hydrodynamics, we have simulated hydrodynamic evolution of QGP fluid with dissipation due to shear viscosity only. Simulation confirms that compared to an ideal fluid, energy density or temperature of…

Nuclear Theory · Physics 2007-05-23 A. K. Chaudhuri

`Entropy' appears as driving force in many different evolution equations, both deterministic and stochastic, and in these equations this `entropy' also takes different forms. We show how all these examples can be understood as different…

Dynamical Systems · Mathematics 2026-03-10 Mark A. Peletier

Classical gradient systems have a linear relation between rates and driving forces. In generalized gradient systems we allow for arbitrary relations derived from general non-quadratic dissipation potentials. This paper describes two natural…

Analysis of PDEs · Mathematics 2018-01-17 Matthias Liero , Alexander Mielke , Mark A. Peletier , D. R. Michiel Renger

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

Thermodynamics teaches that if a system initially off-equilibrium is coupled to work sources, the maximum work that it may yield is governed by its energy and entropy. For finite systems this bound is usually not reachable. The maximum…

Statistical Mechanics · Physics 2009-11-10 A. E. Allahverdyan , R. Balian , Th. M. Nieuwenhuizen

In the last few decades, some hypotheses for entropy production (EP) principles have been forwarded as possible candidates for organizational principles in non-linear non- equilibrium systems. Two important hypotheses will be studied: the…

Chemical Physics · Physics 2007-05-23 Stijn Bruers

The total entropy production and its three constituent components are described both as fluctuating trajectory-dependent quantities and as averaged contributions in the context of the continuous Markovian dynamics, described by stochastic…

Statistical Mechanics · Physics 2015-06-04 Richard E. Spinney , Ian J. Ford

Certain Markov processes, or deterministic evolution equations, have the property that they are dual to a stochastic process that exhibits extinction versus unbounded growth, i.e., the total mass in such a process either becomes zero, or…

Probability · Mathematics 2007-05-23 Jan M. Swart

Collections of self-propelled particles that move persistently by continuously consuming free energy are a paradigmatic example of active matter. In these systems, unlike Brownian "hot colloids", the breakdown of detailed balance yields a…

Soft Condensed Matter · Physics 2018-09-12 Suraj Shankar , M. Cristina Marchetti

The field of complex networks studies a wide variety of interacting systems by representing them as networks. To understand their properties and mutual relations, the randomisation of network connections is a commonly used tool. However,…

Statistical Mechanics · Physics 2024-10-18 Noam Abadi , Franco Ruzzenenti

By using entropy and entropy production, we calculate the steady flux of some phenomena. The method we use is a competition method, $S_S/\tau+\sigma={\it maximum}$, where $S_S$ is system entropy, $\sigma$ is entropy production and $\tau$ is…

Statistical Mechanics · Physics 2016-07-26 Yong-Jun Zhang

Gradient Descent (GD) is a ubiquitous algorithm for finding the optimal solution to an optimization problem. For reduced computational complexity, the optimal solution $\mathrm{x^*}$ of the optimization problem must be attained in a minimum…

Optimization and Control · Mathematics 2023-06-01 Revati Gunjal , Sushama Wagh , Syed Shadab Nayyer , Alex Stankovic , Navdeep M. Singh

The interrelationships of the fundamental biological processes natural selection, mutation, and stochastic drift are quantified by the entropy rate of Moran processes with mutation, measuring the long-run variation of a Markov process. The…

Dynamical Systems · Mathematics 2014-01-14 Marc Harper

Isolating slower dynamics from fast fluctuations has proven remarkably powerful, but how do we proceed from partial observations of dynamical systems for which we lack underlying equations? Here, we construct maximally-predictive states by…

Biological Physics · Physics 2023-02-28 Antonio Carlos Costa , Tosif Ahamed , David Jordan , Greg Stephens

We show that the principle of maximum entropy, a variational method appearing in statistical inference, statistical physics, and the analysis of stochastic dynamical systems, admits a geometric description from gauge theory. Using the…

Mathematical Physics · Physics 2023-01-05 Dalton A R Sakthivadivel

Entropy serves as a central observable in equilibrium thermodynamics. However, many biological and ecological systems operate far from thermal equilibrium. Here we show that entropy production can characterize the behavior of such…

Statistical Mechanics · Physics 2015-03-17 Benjamin Andrae , Jonas Cremer , Tobias Reichenbach , Erwin Frey

Fluctuating entropy production is studied for a set of linearly coupled complex fields. The general result is applied to non-equilibrium fluctuating hydrodynamic equations for coarse-grained fields (density, temperature and velocity), in…

Statistical Mechanics · Physics 2012-07-09 Giacomo Gradenigo , Andrea Puglisi , Alessandro Sarracino

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

Variational principles play a fundamental role in deriving evolution equations of physics. They are working well in case of nondissipative evolution but for dissipative systems they are not unique, not predictive and not constructive. With…

Statistical Mechanics · Physics 2020-09-02 Péter Ván , Róbert Kovács

Autoregressive generative models -- including Transformers, recurrent neural networks, classical Kalman filters, state space models, and Mamba -- all generate sequences by sampling each output from a deterministic summary of the past,…

Statistical Mechanics · Physics 2026-04-17 Takahiro Sagawa