A Cyclic Low-Rank Smith Method for Large Sparse Lyapunov Equations
SIAM Journal on Scientific Computing
Low Rank Solution of Lyapunov Equations
SIAM Journal on Matrix Analysis and Applications
Product form approximations for communicating Markov processes
Performance Evaluation
Krylov Subspace Methods for Linear Systems with Tensor Product Structure
SIAM Journal on Matrix Analysis and Applications
Approximation of $2^d\times2^d$ Matrices Using Tensor Decomposition
SIAM Journal on Matrix Analysis and Applications
A Fourth Order Hermitian Box-Scheme with Fast Solver for the Poisson Problem in a Square
Journal of Scientific Computing
Dynamical Tensor Approximation
SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Scientific Computing
Low-Rank Tensor Krylov Subspace Methods for Parametrized Linear Systems
SIAM Journal on Matrix Analysis and Applications
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In this paper we construct an approximation to the solution x of a linear system of equations Ax=b of tensor product structure as it typically arises for finite element and finite difference discretisations of partial differential operators on tensor grids. For a right-hand side b of tensor product structure we can prove that the solution x can be approximated by a sum of O(log(ε)2) tensor product vectors where ε is the relative approximation error. Numerical examples for systems of size 1024256 indicate that this method is suitable for high-dimensional problems.