• Media type: E-Book; Report; Text
  • Title: On the relation between gradient flows and the large-deviation principle, with applications to Markov chains and diffusion
  • Contributor: Mielke, Alexander [Author]; Peletier, Mark A. [Author]; Renger, D. R. Michiel [Author]
  • imprint: Weierstrass Institute for Applied Analysis and Stochastics publication server, 2013
  • Language: English
  • DOI: https://doi.org/10.20347/WIAS.PREPRINT.1868
  • Keywords: 49S05 ; 60J25 ; 35Q82 ; article ; 35Q84 ; 60J27 ; Generalized gradient flows -- large deviations -- convex analysis -- particle systems ; 60F10
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  • Description: Motivated by the occurence in rate functions of time-dependent large-deviation principles, we study a class of non-negative functions ℒ that induce a flow, given by ℒ(zt,żt)=0. We derive necessary and sufficient conditions for the unique existence of a generalized gradient structure for the induced flow, as well as explicit formulas for the corresponding driving entropy and dissipation functional. In particular, we show how these conditions can be given a probabilistic interpretation when ℒ is associated to the large deviations of a microscopic particle system. Finally, we illustrate the theory for independent Brownian particles with drift, which leads to the entropy-Wasserstein gradient structure, and for independent Markovian particles on a finite state space, which leads to a previously unknown gradient structure.