Regularity and convergence analysis in Sobolev and Hölder spaces for generalized Whittle-Matérn fields
Provides rigorous convergence guarantees for approximating Gaussian random fields with fractional elliptic operators, benefiting uncertainty quantification and spatial statistics.
The paper proves optimal convergence rates for spectral and finite element approximations of generalized Whittle-Matérn fields in Sobolev and Hölder norms, with covariance error converging more than twice as fast. Numerical experiments confirm the theory.
We analyze several Galerkin approximations of a Gaussian random field $\mathcal{Z}\colon\mathcal{D}\timesΩ\to\mathbb{R}$ indexed by a Euclidean domain $\mathcal{D}\subset\mathbb{R}^d$ whose covariance structure is determined by a negative fractional power $L^{-2β}$ of a second-order elliptic differential operator $L:= -\nabla\cdot(A\nabla) + κ^2$. Under minimal assumptions on the domain $\mathcal{D}$, the coefficients $A\colon\mathcal{D}\to\mathbb{R}^{d\times d}$, $κ\colon\mathcal{D}\to\mathbb{R}$, and the fractional exponent $β>0$, we prove convergence in $L_q(Ω; H^σ(\mathcal{D}))$ and in $L_q(Ω; C^δ(\overline{\mathcal{D}}))$ at (essentially) optimal rates for (i) spectral Galerkin methods and (ii) finite element approximations. Specifically, our analysis is solely based on $H^{1+α}(\mathcal{D})$-regularity of the differential operator $L$, where $0<α\leq 1$. For this setting, we furthermore provide rigorous estimates for the error in the covariance function of these approximations in $L_{\infty}(\mathcal{D}\times\mathcal{D})$ and in the mixed Sobolev space $H^{σ,σ}(\mathcal{D}\times\mathcal{D})$, showing convergence which is more than twice as fast compared to the corresponding $L_q(Ω; H^σ(\mathcal{D}))$-rate. For the well-known example of such Gaussian random fields, the original Whittle-Matérn class, where $L=-Δ+ κ^2$ and $κ\equiv \operatorname{const.}$, we perform several numerical experiments which validate our theoretical results.