Quenched large deviations for interacting diffusions in random media
Eric Lu\c{c}on

TL;DR
This paper establishes a quenched large deviation principle for the empirical measure of mean-field interacting diffusions in a fixed random environment, revealing a disorder-independent rate function.
Contribution
It provides the first quenched LDP for interacting diffusions in random media, with a novel rate function differing from the averaged case.
Findings
LDP holds for every fixed environment realization
Rate function is independent of the disorder
Results extend to empirical flow and local measures
Abstract
The aim of the paper is to establish a large deviation principle (LDP) for the empirical measure of mean-field interacting diffusions in a random environment. The point is to derive such a result once the environment has been frozen (quenched model). The main theorem states that a LDP holds for every realization of the environment, with a rate function that does not depend on the disorder and is different from the rate function in the averaged model. Similar results concerning the empirical flow and local empirical measures are provided.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
