Geometric shape of invariant manifolds for a class of stochastic partial differential equations

TL;DR

This paper investigates the geometric shape of invariant manifolds in a class of stochastic partial differential equations with multiplicative noise, providing local approximations and comparisons with deterministic cases.

Contribution

It offers the first description of the local geometric shape of invariant manifolds for stochastic PDEs with multiplicative noise, enhancing understanding of their structure.

Findings

Local geometric shape approximations of invariant manifolds

Comparison with deterministic PDE invariant manifolds

Probabilistic likelihood of approximation accuracy

Abstract

Invariant manifolds play an important role in the study of the qualitative dynamical behaviors for nonlinear stochastic partial differential equations. However, the geometric shape of these manifolds is largely unclear. The purpose of the present paper is to try to describe the geometric shape of invariant manifolds for a class of stochastic partial differential equations with multiplicative white noises. The local geometric shape of invariant manifolds is approximated, which holds with significant likelihood. Furthermore, the result is compared with that for the corresponding deterministic partial differential equations.