Abstract
This paper consists of two parts. In the first part, we focus on the average of a functional over shifted Gaussian homogeneous noise and as the averaging domain covers the whole space, we establish a Breuer-Major type Gaussian fluctuation based on various assumptions on the covariance kernel and/or the spectral measure. Our methodology for the first part begins with the application of Malliavin calculus around Nualart-Peccati's Fourth Moment Theorem, and in addition we apply the Fourier techniques as well as a soft approximation argument based on Bessel functions of first kind. The same methodology leads us to investigate a closely related problem in the second part. We study the spatial average of a linear stochastic heat equation driven by space-time Gaussian colored noise. The temporal covariance kernel $\gamma_0$ is assumed to be locally integrable in this paper. If the spatial covariance kernel is nonnegative and integrable on the whole space, then the spatial average admits Gaussian fluctuation; with some extra mild integrability condition on $\gamma_0$, we are able to provide a functional central limit theorem. These results complement recent studies on the spatial average for SPDEs. Our analysis also allows us to consider the case where the spatial covariance kernel is not integrable: For example, in the case of the Riesz kernel, the first chaotic component of the spatial average is dominant so that the Gaussian fluctuation also holds true.
Highlights
Where σ(R) is a normalization constant and N (m, v2) stands for a real normal distribution with mean m and variance v2. To illustrate how this spatial averaging is related to the aforementioned Breuer-Major theorem and to give a flavor of our results, we provide below a particular case
We provide sufficient conditions for (1.4) in terms of the spectral measure
The random variable may depend on infinitely many coordinates, which shall be distinguished from the classical Breuer-Major theorem
Summary
We introduce some notation for later reference and we provide several lemmas needed for our proofs. We obtain the following inequalities: φ∗p ∞ = φ ∗ φ∗p−1 ∞ ≤ φ Lq(Rd) φ∗p−1 Lq1 (Rd) with q1 = p, φ∗p−1 = Lq1 (Rd) φ ∗ φ∗p−2 ≤ Lq1 (Rd) φ Lq(Rd) φ∗p−2 Lq2 (Rd) with q2 = p/2, φ∗p−2 = Lq2 (Rd) φ ∗ φ∗p−3 ≤ Lq2 (Rd) φ Lq(Rd) φ∗p−3 Lq3 (Rd) with q3 = p/3, φ∗2 = Lqp−2 (Rd). The random variable may depend on infinitely many coordinates, which shall be distinguished from the classical Breuer-Major theorem
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