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B1333
Title: High-frequency analysis of parabolic stochastic PDEs Authors:  Carsten Chong - HKUST (Hong Kong) [presenting]
Abstract: The focus is on the stochastic heat equation driven by an additive or multiplicative Gaussian noise that is white in time and spatially homogeneous in space. Assuming that the spatial correlation function is given by a Riesz kernel of order $\alpha$, we prove a central limit theorem for the power variations of the solution in the additive case. We further show that the same central limit theorem is valid with multiplicative noise if $\alpha\in(0,1)$ but fails in general if $\alpha=1$ (and $d \geq 2$) or if the noise is a space-time white noise (and $d = 1$). We discuss our results in the context of statistical estimation for the stochastic heat equation.