Exponential mixing for the stochastic Allen--Cahn equation with localized white noise

TL;DR

This paper proves exponential mixing and uniqueness of invariant measures for the 1D stochastic Allen--Cahn equation driven by localized white noise, using PDE control theory techniques.

Contribution

It introduces a novel approach combining stabilization and controllability methods to analyze the global dynamics under localized noise.

Findings

Proves the existence of a unique invariant measure.

Establishes exponential mixing of the Markov process.

Develops PDE control techniques for stochastic PDE analysis.

Abstract

This paper studies the 1D stochastic Allen--Cahn equation on a bounded domain driven by localized white noise. We prove that the associated Markov process admits a unique invariant measure and is exponential mixing. The main challenge lies in the interaction between localized nature of the noise and non-trivial global dynamics of the system. To overcome this, our approach relies on two ingredients from PDE control theory: stabilization for the linearized system and global steady-state controllability for the nonlinear equation. The stabilization result is derived using the weak observability and Fenchel--Rockafellar duality, while the global controllability relies on quasi-static deformations combined with global dynamics.