Large Deviations for Finite State Markov Jump Processes with Mean-Field Interaction Via the Comparison Principle for an Associated Hamilton–Jacobi Equation

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Abstract

We prove the large deviation principle (LDP) for the trajectory of a broad class of finite state mean-field interacting Markov jump processes via a general analytic approach based on viscosity solutions. Examples include generalized Ehrenfest models as well as Curie–Weiss spin flip dynamics with singular jump rates. The main step in the proof of the LDP, which is of independent interest, is the proof of the comparison principle for an associated collection of Hamilton–Jacobi equations. Additionally, we show that the LDP provides a general method to identify a Lyapunov function for the associated McKean–Vlasov equation.
Original languageEnglish
Pages (from-to)321-345
Number of pages25
JournalJournal of Statistical Physics
Volume164
Issue number2
DOIs
Publication statusPublished - 2016

Keywords

  • Large deviations
  • Non-linear jump processes
  • Hamilton–Jacobi equation
  • Viscosity solutions
  • Comparison principle

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