A structure-preserving low-rank factorization of 2RDMs achieves linear rank scaling with system size and ~99% compression while retaining chemical accuracy for correlated states.
Journal of Chemical Theory and Computation , title =
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Perspective reviewing TTNS-DMRG methods for computing thousands of vibrational eigenstates in molecules up to 33 dimensions, with emphasis on connections to ML-MCTDH and practical challenges.
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Low-rank compression of two-electron reduced density matrices
A structure-preserving low-rank factorization of 2RDMs achieves linear rank scaling with system size and ~99% compression while retaining chemical accuracy for correlated states.
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Accurate, full-dimensional computations of thousands of complex vibrational eigenstates with tree tensor network states
Perspective reviewing TTNS-DMRG methods for computing thousands of vibrational eigenstates in molecules up to 33 dimensions, with emphasis on connections to ML-MCTDH and practical challenges.