Central limit theorems for stochastic wave equations in high dimensions

We consider stochastic wave equations in spatial dimensions d≥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 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.

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Publication Details

Journal
Electronic Journal of Probability
Published
2025-01-01
DOI
https://doi.org/10.1214/25-ejp1319
Citations
2
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
4.42

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article

Central limit theorems for stochastic wave equations in high dimensions

Masahisa Ebina
2 citations
Electronic Journal of Probability
Stochastic processes and financial applications
4.42
article

Central limit theorems for stochastic wave equations in high dimensions

Masahisa Ebina
article en
2 citations

Abstract

We consider stochastic wave equations in spatial dimensions d≥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 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.

Electronic Journal of ProbabilityVol. 30(none)
Kyoto University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 7%
Stochastic processes and financial applications
4.42
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