The Small-Noise Limit of the Most Likely Element is the Most Likely Element in the Small-Noise Limit

TL;DR

This paper establishes the convergence of the Onsager-Machlup function to the Freidlin-Wentzell function in the small-noise limit for infinite-dimensional Gaussian measures, clarifying the relationship between these two key functions.

Contribution

It demonstrates the pointwise and Γ-convergence of the Onsager-Machlup function to the Freidlin-Wentzell function in the small-noise limit for infinite-dimensional measures.

Findings

Proves convergence of Onsager-Machlup to Freidlin-Wentzell functions

Provides explicit expressions for the limits

Applies results to path-dependent SDEs and infinite algebraic systems

Abstract

In this paper, we study the Onsager-Machlup function and its relationship to the Freidlin-Wentzell function for measures equivalent to arbitrary infinite dimensional Gaussian measures. The Onsager-Machlup function can serve as a density on infinite dimensional spaces, where a uniform measure does not exist, and has been seen as the Lagrangian for the ``most likely element". The Freidlin-Wentzell rate function is the large deviations rate function for small-noise limits and has also been identified as a Lagrangian for the ``most likely element". This leads to a conundrum - what is the relationship between these two functions? We show both pointwise and $\Gamma$-convergence (which is essentially the convergence of minimizers) of the Onsager-Machlup function under the small-noise limit to the Freidlin-Wentzell function - and give an expression for both. That is, we show that the small-noise limit of the most likely element is the most likely element in the small noise limit for infinite dimensional measures that are equivalent to a Gaussian. Examples of measures include the law of solutions to path-dependent stochastic differential equations and the law of an infinite system of random algebraic equations.