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arXiv 2007.15148math.PR
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随机分数阶heat equation的定量正态逼近

Quantitative normal approximations for the stochastic fractional heat equation

Obayda Assaad, David Nualart, Ciprian A. Tudor, Lauri Viitasaari

摘要:

本文给出了一般高斯乘性噪声驱动的随机分数阶热方程的{ \it定量}中心极限定理,包括时空白噪声和空间协方差由里斯核或有界可积函数给出的白色噪声的情形.我们表明,在一个球的半径$R$的空间平均收敛,作为$R$趋于无穷大,经过适当的重整化,朝着高斯极限的全变差的距离。我们还提供了一个泛函中心极限定理。因此,我们最近证明了类似的结果随机热方程的情况下的分数拉普拉斯算子和一般的噪声。

英文摘要:

In this article we present a {\it 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.

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