Convergence analysis for minimum action methods coupled with a finite difference method

Fuente: arXiv
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Autores principales: Hong, Jialin, Jin, Diancong, Sheng, Derui
Formato: Preprint
Publicado: 2021
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author Hong, Jialin
Jin, Diancong
Sheng, Derui
author_facet Hong, Jialin
Jin, Diancong
Sheng, Derui
contents The minimum action method (MAM) is an effective approach to numerically solving minimums and minimizers of Freidlin--Wentzell (F-W) action functionals, which is used to study the most probable transition path and probability of the occurrence of transitions for stochastic differential equations (SDEs) with small noise. In this paper, we focus on MAMs based on a finite difference method, and present the convergence analysis of minimums and minimizers of the discrete F-W action functional. The main result shows that the convergence orders of the minimum of the discrete F-W action functional in the cases of multiplicative noises and additive noises are $1/2$ and $1$, respectively. Our main result also reveals the convergence of the stochastic $θ$-method for SDEs with small noise in terms of large deviations.
format Preprint
id arxiv_https___arxiv_org_abs_2102_04061
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Convergence analysis for minimum action methods coupled with a finite difference method
Hong, Jialin
Jin, Diancong
Sheng, Derui
Probability
Numerical Analysis
The minimum action method (MAM) is an effective approach to numerically solving minimums and minimizers of Freidlin--Wentzell (F-W) action functionals, which is used to study the most probable transition path and probability of the occurrence of transitions for stochastic differential equations (SDEs) with small noise. In this paper, we focus on MAMs based on a finite difference method, and present the convergence analysis of minimums and minimizers of the discrete F-W action functional. The main result shows that the convergence orders of the minimum of the discrete F-W action functional in the cases of multiplicative noises and additive noises are $1/2$ and $1$, respectively. Our main result also reveals the convergence of the stochastic $θ$-method for SDEs with small noise in terms of large deviations.
title Convergence analysis for minimum action methods coupled with a finite difference method
topic Probability
Numerical Analysis
url https://arxiv.org/abs/2102.04061