Entropic divergence and entropy related to nonlinear master equations

Tamás Sándor Biró, Zoltán Néda, András Telcs

Research output: Contribution to journalArticle

1 Citation (Scopus)


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.

Original languageEnglish
Article number993
Issue number10
Publication statusPublished - Oct 1 2019


  • Entropic divergence
  • Entropy
  • Master equation
  • Preferential growth
  • Reset

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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