Semilinear stochastic partial differential equations: central limit theorem and moderate deviations

2019/03/30 by Rangrang Zhang, Jie Xiong, Zhang, Rangrang +1
Economics, Econometrics and Finance · Engineering · Mathematics · #FOS: Mathematics #Mathematical Biology Tumor Growth #Probability (math.PR) #Stability and Controllability of Differential Equations #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1904.00299

openalex publication_date 2019/03/30 · openalex created_date 2019/04/11 · openalex updated_date 2026/08/01

Abstract

In this paper, we establish a central limit theorem (CLT) and the moderate deviation principles (MDP) for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain. The main results can be applied to stochastic partial differential equations of various types such as the stochastic Burgers equation and the reaction-diffusion equations perturbed by space-time white noise.

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