Central limit theorems for stochastic wave equations in high dimensions

Fuente: arXiv
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Main Author: Ebina, Masahisa
Format: Preprint
Published: 2023
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author Ebina, Masahisa
author_facet Ebina, Masahisa
contents We consider stochastic wave equations in spatial dimensions $d \geq 4$. We assume that the driving noise is given by a Gaussian noise that is white in time and has some spatial correlation. When the spatial correlation is given by the Riesz kernel, we also establish that the spatial integral of the solution with proper normalization converges to the standard normal distribution under the Wasserstein distance. The convergence is obtained by first constructing the approximation sequence to the solution and then applying Malliavin-Stein's method to the normalized spatial integral of the sequence. The corresponding functional central limit theorem is presented as well.
format Preprint
id arxiv_https___arxiv_org_abs_2308_05716
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Central limit theorems for stochastic wave equations in high dimensions
Ebina, Masahisa
Probability
60F05, 60G15, 60H07, 60H15
We consider stochastic wave equations in spatial dimensions $d \geq 4$. We assume that the driving noise is given by a Gaussian noise that is white in time and has some spatial correlation. When the spatial correlation is given by the Riesz kernel, we also establish that the spatial integral of the solution with proper normalization converges to the standard normal distribution under the Wasserstein distance. The convergence is obtained by first constructing the approximation sequence to the solution and then applying Malliavin-Stein's method to the normalized spatial integral of the sequence. The corresponding functional central limit theorem is presented as well.
title Central limit theorems for stochastic wave equations in high dimensions
topic Probability
60F05, 60G15, 60H07, 60H15
url https://arxiv.org/abs/2308.05716