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Universal Gorban’s Entropies: Geometric Case Study

Recently, A.N. Gorban presented a rich family of universal Lyapunov functions for any linear or non-linear reaction network with detailed or complex balance. Two main elements of the construction algorithm are partial equilibria of reactions and convex envelopes of families of functions. These new f...

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Autor principal: Mirkes, Evgeny M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516716/
https://www.ncbi.nlm.nih.gov/pubmed/33286038
http://dx.doi.org/10.3390/e22030264
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author Mirkes, Evgeny M.
author_facet Mirkes, Evgeny M.
author_sort Mirkes, Evgeny M.
collection PubMed
description Recently, A.N. Gorban presented a rich family of universal Lyapunov functions for any linear or non-linear reaction network with detailed or complex balance. Two main elements of the construction algorithm are partial equilibria of reactions and convex envelopes of families of functions. These new functions aimed to resolve “the mystery” about the difference between the rich family of Lyapunov functions (f-divergences) for linear kinetics and a limited collection of Lyapunov functions for non-linear networks in thermodynamic conditions. The lack of examples did not allow to evaluate the difference between Gorban’s entropies and the classical Boltzmann–Gibbs–Shannon entropy despite obvious difference in their construction. In this paper, Gorban’s results are briefly reviewed, and these functions are analysed and compared for several mechanisms of chemical reactions. The level sets and dynamics along the kinetic trajectories are analysed. The most pronounced difference between the new and classical thermodynamic Lyapunov functions was found far from the partial equilibria, whereas when some fast elementary reactions became close to equilibrium then this difference decreased and vanished in partial equilibria.
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spelling pubmed-75167162020-11-09 Universal Gorban’s Entropies: Geometric Case Study Mirkes, Evgeny M. Entropy (Basel) Article Recently, A.N. Gorban presented a rich family of universal Lyapunov functions for any linear or non-linear reaction network with detailed or complex balance. Two main elements of the construction algorithm are partial equilibria of reactions and convex envelopes of families of functions. These new functions aimed to resolve “the mystery” about the difference between the rich family of Lyapunov functions (f-divergences) for linear kinetics and a limited collection of Lyapunov functions for non-linear networks in thermodynamic conditions. The lack of examples did not allow to evaluate the difference between Gorban’s entropies and the classical Boltzmann–Gibbs–Shannon entropy despite obvious difference in their construction. In this paper, Gorban’s results are briefly reviewed, and these functions are analysed and compared for several mechanisms of chemical reactions. The level sets and dynamics along the kinetic trajectories are analysed. The most pronounced difference between the new and classical thermodynamic Lyapunov functions was found far from the partial equilibria, whereas when some fast elementary reactions became close to equilibrium then this difference decreased and vanished in partial equilibria. MDPI 2020-02-25 /pmc/articles/PMC7516716/ /pubmed/33286038 http://dx.doi.org/10.3390/e22030264 Text en © 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mirkes, Evgeny M.
Universal Gorban’s Entropies: Geometric Case Study
title Universal Gorban’s Entropies: Geometric Case Study
title_full Universal Gorban’s Entropies: Geometric Case Study
title_fullStr Universal Gorban’s Entropies: Geometric Case Study
title_full_unstemmed Universal Gorban’s Entropies: Geometric Case Study
title_short Universal Gorban’s Entropies: Geometric Case Study
title_sort universal gorban’s entropies: geometric case study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516716/
https://www.ncbi.nlm.nih.gov/pubmed/33286038
http://dx.doi.org/10.3390/e22030264
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