Abstract
For Au = f with an elliptic differential operator \({A:\mathcal{H} \rightarrow \mathcal{H}'}\) and stochastic data f, the m-point correlation function \({{\mathcal M}^m u}\) of the random solution u satisfies a deterministic equation with the m-fold tensor product operator A (m) of A. Sparse tensor products of hierarchic FE-spaces in \({\mathcal{H}}\) are known to allow for approximations to \({{\mathcal M}^m u}\) which converge at essentially the rate as in the case m = 1, i.e. for the deterministic problem. They can be realized by wavelet-type FE bases (von Petersdorff and Schwab in Appl Math 51(2):145–180, 2006; Schwab and Todor in Computing 71:43–63, 2003). If wavelet bases are not available, we show here how to achieve the fast computation of sparse approximations of \({{\mathcal M}^m u}\) for Galerkin discretizations of A by multilevel frames such as BPX or other multilevel preconditioners of any standard FEM approximation for A. Numerical examples illustrate feasibility and scope of the method.
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Harbrecht, H., Schneider, R. & Schwab, C. Multilevel frames for sparse tensor product spaces. Numer. Math. 110, 199–220 (2008). https://doi.org/10.1007/s00211-008-0162-x
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DOI: https://doi.org/10.1007/s00211-008-0162-x