The paper analyzes a preconditioned inverse iteration solver with rank truncation for low-rank MPS approximations to eigenfunctions and generalizes it to subspace iteration, with numerical tests on model problems.
56, Springer, Cham, 2019, Second edition
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Low-rank eigenvalue solvers for block-sparse matrix product states
The paper analyzes a preconditioned inverse iteration solver with rank truncation for low-rank MPS approximations to eigenfunctions and generalizes it to subspace iteration, with numerical tests on model problems.