On Asymptotic Preserving schemes for a class of Stochastic Differential Equations in averaging and diffusion approximation regimes

TL;DR

This paper develops Asymptotic Preserving schemes for slow-fast stochastic differential equations, ensuring correct limiting behavior in averaging and diffusion regimes, with proven consistency and uniform accuracy demonstrated through numerical experiments.

Contribution

It introduces a new class of schemes that remain accurate in the limit of vanishing time-scale separation, addressing failures of crude schemes in capturing correct limits.

Findings

Schemes are consistent in distribution with limiting SDEs.

Numerical experiments confirm the schemes' effectiveness.

Error estimates show uniform accuracy in the averaging regime.

Abstract

We introduce and study a notion of Asymptotic Preserving schemes, related to convergence in distribution, for a class of slow-fast Stochastic Differential Equations. In some examples, crude schemes fail to capture the correct limiting equation resulting from averaging and diffusion approximation procedures. We propose examples of Asymptotic Preserving schemes: when the time-scale separation vanishes, one obtains a limiting scheme, which is shown to be consistent in distribution with the limiting Stochastic Differential Equation. Numerical experiments illustrate the importance of the proposed Asymptotic Preserving schemes for several examples. In addition, in the averaging regime, error estimates are obtained and the proposed scheme is proved to be uniformly accurate.