June 2022 Large deviations of mean-field interacting particle systems in a fast varying environment
Sarath Yasodharan, Rajesh Sundaresan
Author Affiliations +
Ann. Appl. Probab. 32(3): 1666-1704 (June 2022). DOI: 10.1214/21-AAP1718

Abstract

This paper studies large deviations of a “fully coupled” finite state mean-field interacting particle system in a fast varying environment. The empirical measure of the particles evolves in the slow time scale and the random environment evolves in the fast time scale. Our main result is the path-space large deviation principle for the joint law of the empirical measure process of the particles and the occupation measure process of the fast environment. This extends previous results known for two time scale diffusions to two time scale mean-field models with jumps. Our proof is based on the method of stochastic exponentials. We characterise the rate function by studying a certain variational problem associated with an exponential martingale.

Funding Statement

The authors were supported by a grant from the Indo–French Centre for Applied Mathematics on a project titled “Metastability phenomena in algorithms and engineered systems”. The first author was supported by a fellowship grant from the Centre for Networked Intelligence (a Cisco CSR initiative), Indian Institute of Science, Bangalore.

Citation

Download Citation

Sarath Yasodharan. Rajesh Sundaresan. "Large deviations of mean-field interacting particle systems in a fast varying environment." Ann. Appl. Probab. 32 (3) 1666 - 1704, June 2022. https://doi.org/10.1214/21-AAP1718

Information

Received: 1 August 2020; Published: June 2022
First available in Project Euclid: 29 May 2022

MathSciNet: MR4429998
zbMATH: 1496.60025
Digital Object Identifier: 10.1214/21-AAP1718

Subjects:
Primary: 60F10
Secondary: 60J75 , 60K35 , 60K37

Keywords: averaging principle , large deviations , Mean-field interaction , metastability , time scale separation

Rights: Copyright © 2022 Institute of Mathematical Statistics

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Vol.32 • No. 3 • June 2022
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