Path large deviations for interacting diffusions with local mean-field interactions in random environment

TL;DR

This paper establishes a large deviation principle for a system of interacting spins in a random environment, accounting for space, environment dependence, and multiple approaches to derive the rate function.

Contribution

It extends large deviation analysis to local mean-field interactions in random environments, generalizing Dawson-Gärtner's approach and Varadhan's lemma.

Findings

Proved path large deviation principle for the system.

Derived explicit rate functions for empirical processes and measures.

Introduced new methods to handle space and environment dependencies.

Abstract

We consider a system of $N^{d}$ spins in random environment with a random local mean field type interaction. Each spin has a fixed spatial position on the torus $\mathbb{T}^{d}$, an attached random environment and a spin value in $\mathbb{R}$ that evolves according to a space and environment dependent Langevin dynamic. The interaction between two spins depends on the spin values, on the spatial distance and the random environment of both spins. We prove the path large deviation principle from the hydrodynamic (or local mean field McKean-Vlasov) limit and derive different expressions of the rate function for the empirical process and for the empirical measure of the paths. To this end, we generalize an approach of Dawson and G\"artner. By the space and random environment dependency, this requires new ingredients compared to mean field type interactions. Moreover, we prove the large deviation principle by using a second approach. This requires a generalisation of Varadhan's lemma to nowhere continuous functions.