Poisson Equations with locally-Lipschitz coefficients and Uniform in Time Averaging for Stochastic Differential Equations via Strong Exponential Stability
Dan Crisan, Paul Dobson, Ben Goddard, Michela Ottobre, Iain Souttar

TL;DR
This paper establishes a novel uniform-in-time averaging result with a convergence rate for multiscale stochastic differential equations with super-linear coefficients, leveraging strong exponential stability to analyze associated Poisson equations.
Contribution
It provides the first UiT averaging result with a convergence rate for fully coupled SDEs with super-linear growth, using SES to handle Poisson equations on non-compact spaces.
Findings
First UiT averaging result with rate for super-linear SDEs
Demonstrates SES as key to analyzing Poisson equations
Applicable to statistical methods and molecular dynamics
Abstract
We study averaging for Stochastic Differential Equations (SDEs) and Poisson equations. We succeed in obtaining a uniform in time (UiT) averaging result, with a rate, for fully coupled SDE models with super-linearly growing coefficients. This is the main result of this paper and is, to the best of our knowledge, the first UiT multiscale result with a rate. Very few UiT averaging results exist in the literature, and they almost exclusively apply to multiscale systems of Ordinary Differential Equations. Among these few, none of those we are aware of comes with a rate of convergence. The UiT nature of this result and the rate of convergence given by the main theorem, make it important as theoretical underpinning for a range of applications, such as applications to statistical methodology, molecular dynamics etc. Key to obtaining both our UiT averaging result and to enable dealing with the…
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