Gaussian fluctuations for the stochastic heat equation with colored noise
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In this paper, we present a quantitative central limit theorem for the d-dimensional stochastic heat equation driven by a Gaussian multiplicative noise, which is white in time and has a spatial covariance given by the Riesz kernel. We show that the spatial average of the solution over an Euclidean ball is close to a Gaussian distribution, when the radius of the ball tends to infinity. Our central limit theorem is described in the total variation distance, using Malliavin calculus and Stein's method. We also provide a functional central limit theorem.
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Spatial ergodicity for SPDEs via Poincar\'e-type inequalities
Solutions to the SPDE ∂_t u = 1/2 Δu + σ(u)η with u(0)≡1 are spatially stationary and ergodic for t>0 under mild decay on the spatial correlation f of the noise.
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