Moderate deviations principle for systems of slow-fast diffusions

TL;DR

This paper establishes the moderate deviations principle for general slow-fast stochastic systems, providing a unified approach applicable to various regimes and noise correlations, with implications for efficient rare event simulation.

Contribution

It introduces a comprehensive method for proving MDP in slow-fast diffusions, accommodating broad coefficient and noise correlation conditions.

Findings

Proves MDP for a wide class of slow-fast systems.

Unifies averaging and homogenization regimes under one framework.

Enables efficient Monte Carlo methods for moderate deviations.

Abstract

In this paper, we prove the moderate deviations principle (MDP) for a general system of slow-fast dynamics. We provide a unified approach, based on weak convergence ideas and stochastic control arguments, that cover both the averaging and the homogenization regimes. We allow the coefficients to be in the whole space and not just the torus and allow the noises driving the slow and fast processes to be correlated arbitrarily. Similar to the large deviation case, the methodology that we follow allows construction of provably efficient Monte Carlo methods for rare events that fall into the moderate deviations regime.