Stability Estimate for an Inverse Stochastic Parabolic Problem of Determining Unknown Time-varying Boundary

TL;DR

This paper establishes a logarithmic stability estimate for determining an unknown moving boundary in a stochastic parabolic equation using interior data, based on a new Carleman estimate, enabling boundary tracking from interior observations.

Contribution

It introduces a novel Carleman estimate for stochastic parabolic equations and proves a logarithmic stability estimate for the inverse boundary problem.

Findings

Logarithmic dependence of boundary on interior data

New Carleman estimate for stochastic equations

Quantitative unique continuation property

Abstract

Stochastic parabolic equations are widely used to model many random phenomena in natural sciences, such as the temperature distribution in a noisy medium, the dynamics of a chemical reaction in a noisy environment, or the evolution of the density of bacteria population. In many cases, the equation may involve an unknown moving boundary which could represent a change of phase, a reaction front, or an unknown population. In this paper, we focus on an inverse problem where the goal is to determine an unknown moving boundary based on data observed in a specific interior subdomain for the stochastic parabolic equation and prove that the unknown boundary depends logarithmically on the interior measurement. This allows us, theoretically, to track and to monitor the behavior of unknown boundary from observation in an arbitrary interior domain. The stability estimate is based on a new Carleman estimate for stochastic parabolic equations. As a byproduct, we obtain a quantitative unique continuation property for stochastic parabolic equations.