Fokker–Planck representations of non-Markov Langevin equations: application to delayed systems
Author(s) -
Luca Giuggioli,
Zohar Neu
Publication year - 2019
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 169
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2018.0131
Subject(s) - statistical physics , fokker–planck equation , markov chain , langevin equation , stochastic differential equation , probabilistic logic , nonlinear system , probability distribution , hierarchy , mathematics , markov process , computer science , partial differential equation , physics , mathematical analysis , quantum mechanics , statistics , economics , market economy
Noise and time delays, or history-dependent processes, play an integral part in many natural and man-made systems. The resulting interplay between random fluctuations and time non-locality are essential features of the emerging complex dynamics in non-Markov systems. While stochastic differential equations in the form of Langevin equations with additive noise for such systems exist, the corresponding probabilistic formalism is yet to be developed. Here we introduce such a framework via an infinite hierarchy of coupled Fokker–Planck equations for then -time probability distribution. When the non-Markov Langevin equation is linear, we show how the hierarchy can be truncated atn = 2 by converting the time non-local Langevin equation to a time-local one with additive coloured noise. We compare the resulting Fokker–Planck equations to an earlier version, solve them analytically and analyse the temporal features of the probability distributions that would allow to distinguish between Markov and non-Markov features.This article is part of the theme issue ‘Nonlinear dynamics of delay systems’.
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