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Entropic Divergence and Entropy Related to Nonlinear Master Equations
We reverse engineer entropy formulas from entropic divergence, optimized to given classes of probability distribution function (PDF) evolution dynamical equation. For linear dynamics of the distribution function, the traditional Kullback–Leibler formula follows from using the logarithm function in t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514324/ http://dx.doi.org/10.3390/e21100993 |
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author | Biró, Tamás Sándor Néda, Zoltán Telcs, András |
author_facet | Biró, Tamás Sándor Néda, Zoltán Telcs, András |
author_sort | Biró, Tamás Sándor |
collection | PubMed |
description | We reverse engineer entropy formulas from entropic divergence, optimized to given classes of probability distribution function (PDF) evolution dynamical equation. For linear dynamics of the distribution function, the traditional Kullback–Leibler formula follows from using the logarithm function in the Csiszár’s f-divergence construction, while for nonlinear master equations more general formulas emerge. As applications, we review a local growth and global reset (LGGR) model for citation distributions, income distribution models and hadron number fluctuations in high energy collisions. |
format | Online Article Text |
id | pubmed-7514324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75143242020-11-09 Entropic Divergence and Entropy Related to Nonlinear Master Equations Biró, Tamás Sándor Néda, Zoltán Telcs, András Entropy (Basel) Article We reverse engineer entropy formulas from entropic divergence, optimized to given classes of probability distribution function (PDF) evolution dynamical equation. For linear dynamics of the distribution function, the traditional Kullback–Leibler formula follows from using the logarithm function in the Csiszár’s f-divergence construction, while for nonlinear master equations more general formulas emerge. As applications, we review a local growth and global reset (LGGR) model for citation distributions, income distribution models and hadron number fluctuations in high energy collisions. MDPI 2019-10-11 /pmc/articles/PMC7514324/ http://dx.doi.org/10.3390/e21100993 Text en © 2019 by the authors. 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 Biró, Tamás Sándor Néda, Zoltán Telcs, András Entropic Divergence and Entropy Related to Nonlinear Master Equations |
title | Entropic Divergence and Entropy Related to Nonlinear Master Equations |
title_full | Entropic Divergence and Entropy Related to Nonlinear Master Equations |
title_fullStr | Entropic Divergence and Entropy Related to Nonlinear Master Equations |
title_full_unstemmed | Entropic Divergence and Entropy Related to Nonlinear Master Equations |
title_short | Entropic Divergence and Entropy Related to Nonlinear Master Equations |
title_sort | entropic divergence and entropy related to nonlinear master equations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514324/ http://dx.doi.org/10.3390/e21100993 |
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