Large deviation principle for reflected SPDE on infinite spatial domain

TL;DR

This paper establishes a large deviation principle for a reflected stochastic partial differential equation on an infinite spatial domain, introducing a new sufficient condition for weak convergence criteria that advances theoretical understanding.

Contribution

It provides a novel sufficient condition for weak convergence in the context of large deviations for reflected SPDEs on infinite domains, extending existing theoretical frameworks.

Findings

Established a large deviation principle for reflected SPDEs on infinite domains

Introduced a new sufficient condition for weak convergence criteria

Enhanced theoretical tools for analyzing reflected SPDEs

Abstract

We study a large deviation principle for a reflected stochastic partial differential equation on infinite spatial domain. A new sufficient condition for the weak convergence criterion proposed by Matoussi, Sabbagh and Zhang ({\it Appl. Math. Optim.} 83: 849-879, 2021) plays an important role in the proof.