An almost sure central limit theorem for the stochastic heat equation

2021 ◽  
pp. 109149
Author(s):  
Jingyu Li ◽  
Yong Zhang
Author(s):  
Obayda Assaad ◽  
David Nualart ◽  
Ciprian A. Tudor ◽  
Lauri Viitasaari

AbstractIn this article we present a quantitative central limit theorem for the stochastic fractional heat equation driven by a a general Gaussian multiplicative noise, including the cases of space–time white noise and the white-colored noise with spatial covariance given by the Riesz kernel or a bounded integrable function. We show that the spatial average over a ball of radius R converges, as R tends to infinity, after suitable renormalization, towards a Gaussian limit in the total variation distance. We also provide a functional central limit theorem. As such, we extend recently proved similar results for stochastic heat equation to the case of the fractional Laplacian and to the case of general noise.


Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Xichao Sun ◽  
Ming Li ◽  
Wei Zhao

We consider a class of stochastic fractional heat equations driven by fractional noises. A central limit theorem is given, and a moderate deviation principle is established.


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