A Particle System with Mean-Field Interaction: Large-Scale Limit of Stationary Distributions

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Abstract

We consider a system consisting of n particles, moving forward in jumps on the real line. System state is the empirical distribution of particle locations. Each particle “jumps forward” at some time points, with the instantaneous rate of jumps given by a decreasing function of the particle’s location quantile within the current state (empirical distribution). Previous work on this model established, under certain conditions, the convergence, as n → ∞, of the system random dynamics to that of a deterministic mean-field model (MFM), which is a solution to an integro-differential equation. Another line of previous work established the existence of MFMs that are traveling waves, as well as the attraction of MFM trajectories to traveling waves. The main results of this paper are: (a) We prove that, as n → ∞, the stationary distributions of (recentered) states concentrate on a (recentered) traveling wave; (b) we obtain a uniform across n moment bound on the stationary distributions of (recentered) states; and (c) we prove a convergence-to-MFM result, which is substantially more general than that in previous work. Results (b) and (c) serve as “ingredients” of the proof of (a), but also are of independent interest.

Original languageEnglish (US)
Pages (from-to)343-359
Number of pages17
JournalStochastic Systems
Volume13
Issue number3
DOIs
StatePublished - Sep 2023

Keywords

  • distributed system synchronization
  • large-scale limit dynamics
  • limit interchange
  • mean-field interaction
  • particle system
  • stationary distribution
  • traveling wave

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

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