Nonlinear approximation theory
Nonlinear approximation theory
Generalized Gaussian Quadratures and Singular Value Decompositions of Integral Operators
SIAM Journal on Scientific Computing
Tensor-product approximation to operators and functions in high dimensions
Journal of Complexity
Journal of Computational and Applied Mathematics
Sparse Spectral Approximations of High-Dimensional Problems Based on Hyperbolic Cross
SIAM Journal on Numerical Analysis
Tensor-Structured Galerkin Approximation of Parametric and Stochastic Elliptic PDEs
SIAM Journal on Scientific Computing
Numerical Solution of the Hartree-Fock Equation in Multilevel Tensor-Structured Format
SIAM Journal on Scientific Computing
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The class of H -matrices allows an approximate matrix arithmetic with almost linear complexity. In the present paper, we apply the H-matrix technique combined with the Kronecker tensor-product approximation (ef. [2. 20]) to represent the inverse of a discrete elliptic operator in a hypercube 0.1 d = Kd on the ease of a high spatial dimension d. In this data-sparse format, we also represent the operator exponential, the fractional power of an elliptic operator as well as the solution operator of the matrix Lyapunov-Sylvester equation. The complexity of our approximations can be estimated by C(dn log2 n) where N - n2 is the discrete problem size.