Far-from-equilibrium time evolution between two gamma distributions

Eun jin Kim, Lucille Marie Tenkès, Rainer Hollerbach, Ovidiu Radulescu

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
36 Downloads (Pure)


Many systems in nature and laboratories are far from equilibrium and exhibit significant fluctuations, invalidating the key assumptions of small fluctuations and short memory time in or near equilibrium. A full knowledge of Probability Distribution Functions (PDFs), especially time-dependent PDFs, becomes essential in understanding far-from-equilibrium processes. We consider a stochastic logistic model with multiplicative noise, which has gamma distributions as stationary PDFs. We numerically solve the transient relaxation problem and show that as the strength of the stochastic noise increases, the time-dependent PDFs increasingly deviate from gamma distributions. For sufficiently strong noise, a transition occurs whereby the PDF never reaches a stationary state, but instead, forms a peak that becomes ever more narrowly concentrated at the origin. The addition of an arbitrarily small amount of additive noise regularizes these solutions and re-establishes the existence of stationary solutions. In addition to diagnostic quantities such as mean value, standard deviation, skewness and kurtosis, the transitions between different solutions are analysed in terms of entropy and information length, the total number of statistically-distinguishable states that a system passes through in time.

Original languageEnglish
Article number511
Issue number10
Publication statusPublished - 22 Sept 2017
Externally publishedYes


  • Fluctuations and noise
  • Fokker-Planck equation
  • Gamma distribution
  • Non-equilibrium statistical mechanics
  • Stochastic processes

ASJC Scopus subject areas

  • Physics and Astronomy(all)


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