Exponential Convergence of Non-Linear Monotone SPDEs

TL;DR

This paper establishes explicit lower bounds for the ultra-exponential convergence rates of certain non-linear monotone SPDEs using coupling methods, with applications to porous medium and p-Laplace equations.

Contribution

It introduces a coupling by change of measure technique to derive explicit convergence rate bounds for non-linear monotone SPDEs, extending previous theoretical results.

Findings

Explicit lower bounds for convergence rates of SPDEs derived.

Applications demonstrated on stochastic porous medium and p-Laplace equations.

Analysis of V-uniform exponential convergence for stochastic fast-diffusion equations.

Abstract

For a Markov semigroup $P_t$ with invariant probability measure $\mu$, a constant $\ll>0$ is called a lower bound of the ultra-exponential convergence rate of $P_t$ to $\mu$, if there exists a constant $C\in (0,\infty)$ such that $$ \sup_{\mu(f^2)\le 1}\|P_tf-\mu(f)\|_\infty \le C \e^{-\ll t},\ \ t\ge 1.$$ By using the coupling by change of measure in the line of [F.-Y. Wang, Ann. Probab. 35(2007), 1333--1350], explicit lower bounds of the ultra-exponential convergence rate are derived for a class of non-linear monotone stochastic partial differential equations. The main result is illustrated by the stochastic porous medium equation and the stochastic $p$-Laplace equation respectively. Finally, the $V$-uniformly exponential convergence is investigated for stochastic fast-diffusion equations.