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Solution of Linear Systems and Matrix Inversion in the TT-Format
Author(s) -
Ivan Oseledets,
Sergey Dolgov
Publication year - 2012
Publication title -
siam journal on scientific computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.674
H-Index - 147
eISSN - 1095-7197
pISSN - 1064-8275
DOI - 10.1137/110833142
Subject(s) - curse of dimensionality , numerical linear algebra , solver , linear algebra , mathematics , density matrix renormalization group , tensor (intrinsic definition) , matrix (chemical analysis) , dimension (graph theory) , algebra over a field , numerical analysis , mathematical optimization , pure mathematics , renormalization group , mathematical analysis , geometry , statistics , materials science , composite material , mathematical physics
Tensors arise naturally in high-dimensional problems in chemistry, financial mathematics, and many other areas. The numerical treatment of such problems is difficult due to the curse of dimensionality: the number of unknowns and the computational complexity grow exponentially with the dimension of the problem. To break the curse of dimensionality, low-parametric representations, or formats, have to be used. In this paper we make use of the TT-format (tensor-train format) which is one of the most effective stable representations of high-dimensional tensors. Basic linear algebra operations in the TT-format are now well developed. Our goal is to provide a “black-box” type of solver for linear systems where both the matrix and the right-hand side are in the TT-format. An efficient DMRG (density matrix renormalization group) method is proposed, and several tricks are employed to make it work. The numerical experiments confirm the effectiveness of our approach.

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