Unique Continuation Property for Stochastic Wave Equations
Qi L\"u, Zhonghua Liao

TL;DR
This paper proves that stochastic wave equations can restore the unique continuation property across characteristic surfaces, a phenomenon that fails in deterministic cases, using a novel stochastic Carleman estimate.
Contribution
It introduces the first proof of UCP for stochastic wave equations across characteristic surfaces, contrasting the deterministic failure, via a new stochastic Carleman estimate.
Findings
UCP holds for stochastic wave equations across characteristic hypersurfaces.
The stochastic Carleman estimate reveals a positive energy contribution from Itô diffusion.
Results differ qualitatively from deterministic wave equations, impacting control and inverse problems.
Abstract
This paper establishes a fundamental and surprising phenomenon in the theory of stochastic wave equations: the restoration of the unique continuation property (UCP) across characteristic hypersurfaces, a property that is known to fail generically in the deterministic setting. We prove that if a solution to a linear stochastic wave equation vanishes on one side of a characteristic surface , then it must vanish in a full neighborhood of any point on , provided the stochastic diffusion coefficient is non-degenerate. This result stands in sharp contrast to the classical H\"ormander-type counterexamples for deterministic waves. Furthermore, we extend the UCP to equations with non-homogeneous stochastic sources and establish a global unique continuation result from the interior of an arbitrarily narrow characteristic cone. Our proofs rely on a novel stochastic Carleman…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStability and Controllability of Differential Equations · Stochastic processes and financial applications · Numerical methods in inverse problems
