Low-rank approximation of continuous functions in Sobolev spaces with dominating mixed smoothness

Michael Griebel; Helmut Harbrecht; Reinhold Schneider

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arXiv · 2203.04100

Low-rank approximation of continuous functions in Sobolev spaces with dominating mixed smoothness

Michael Griebel·Helmut Harbrecht·Reinhold Schneider

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Abstract

Let $\Omega_i\subset\mathbb{R}^{n_i}$, $i=1,\ldots,m$, be given domains. In this article, we study the low-rank approximation with respect to $L^2(\Omega_1\times\dots\times\Omega_m)$ of functions from Sobolev spaces with dominating mixed smoothness. To this end, we first estimate the rank of a bivariate approximation, i.e., the rank of the continuous singular value decomposition. In comparison to the case of functions from Sobolev spaces with isotropic smoothness, compare \cite{GH14,GH19}, we obtain improved results due to the additional mixed smoothness. This convergence result is then used to study the tensor train decomposition as a method to construct multivariate low-rank approximations of functions from Sobolev spaces with dominating mixed smoothness. We show that this approach is able to beat the curse of dimension.

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Michael Griebel, Helmut Harbrecht, Reinhold Schneider. 2022-03-08. Low-rank approximation of continuous functions in Sobolev spaces with dominating mixed smoothness. https://arxiv.org/abs/2203.04100

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