Gradient estimates and domain identification for analytic Ornstein-Uhlenbeck operators

TL;DR

This paper derives gradient estimates and identifies the domain of Ornstein-Uhlenbeck operators in Banach spaces, with applications to stochastic PDEs like the 1D heat equation driven by white noise.

Contribution

It provides new L^p-bounds for the gradient of the Ornstein-Uhlenbeck semigroup and explicitly characterizes the generator's domain under analyticity assumptions.

Findings

Established L^p-gradient bounds for Ornstein-Uhlenbeck semigroups.

Explicitly determined the generator's domain in specific Banach space settings.

Applied results to the stochastic heat equation with additive white noise.

Abstract

Let (P(t)) be the Ornstein-Uhlenbeck semigroup associated with the stochastic Cauchy problem dU(t) = AU(t)dt + dW_H(t), where A is the generator of a C_0-semigroup (S(t)) on a Banach space E, H is a Hilbert subspace of E, and (W_H(t)) is an H-cylindrical Brownian motion. Assuming that (S(t)) restricts to a C_0-semigroup on H, we obtain L^p-bounds for the gradient D_H P(t). We show that if (P(t)) is analytic, then the invariance assumption is fulfilled. As an application we determine the L^p-domain of the generator of (P(t)) explicitly in the case where (S(t)) restricts to a C_0-semigroup on H which is similar to an analytic contraction semigroup. The results are applied to the 1D stochastic heat equation driven by additive space-time white noise.