arXiv Analytics

Sign in

arXiv:2205.13105 [math.PR]AbstractReferencesReviewsResources

Central limit theorems for heat equation with time-independent noise: the regular and rough cases

Raluca M. Balan, Wangjun Yuan

Published 2022-05-26Version 1

In this article, we investigate the asymptotic behaviour of the spatial integral of the solution to the parabolic Anderson model with time independent noise in dimension $d\geq 1$, as the domain of the integral becomes large. We consider 3 cases: (a) the case when the noise has an integrable covariance function; (b) the case when the covariance of the noise is given by the Riesz kernel; (c) the case of the rough noise, i.e. fractional noise with index $H \in (\frac{1}{4},\frac{1}{2})$ in dimension $d=1$. In each case, we identify the order of magnitude of the variance of the spatial integral, we prove a quantitative central limit theorem for the normalized spatial integral by estimating its total variation distance to a standard normal distribution, and we give the corresponding functional limit result.

Related articles: Most relevant | Search more
arXiv:1704.05530 [math.PR] (Published 2017-04-15)
Nonstandard Martingales, Markov Chains and the Heat Equation
arXiv:1105.4485 [math.PR] (Published 2011-05-23)
A quantitative central limit theorem for the random walk among random conductances
arXiv:1205.5403 [math.PR] (Published 2012-05-24, updated 2012-09-24)
A quantitative central limit theorem for linear statistics of random matrix eigenvalues