SIAM Journal on Scientific Computing · 2012 · 195 citations · 29 references
Natural SciencesChemistryMathematicsComputational ChemistryComputational PhysicsRepresentation TheoryDensity Matrix FormalismDimensionality ReductionLinear AlgebraMatrix ComputationNumerical AnalysisNumerical Linear AlgebraComputational Linear AlgebraDensity Matrix Renormalization Group In Quantum ChemistryLinear System SolversMatrix RepresentationsNumerical SimulationRenormalization GroupRenormalization Group Theory
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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Tensor Decompositions and Applications
Tamara G. Kolda, Brett W. Bader · SIAM Review · 2009 · 10.5K citations
Some Mathematical Notes on Three-Mode Factor Analysis
Ledyard R Tucker · Psychometrika · 1966 · 4.3K citations