A structure-preserving low-rank factorization of 2RDMs achieves linear effective rank scaling with ~99% compression for octane while retaining chemical accuracy and enabling quadratic-memory interpolation in ab initio workflows.
Journal of Chemical Theory and Computation , title =
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
physics.chem-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Tree tensor network states combined with DMRG allow accurate full-dimensional computations of thousands of vibrational eigenstates for molecules ranging from small benchmarks to 33-dimensional protonated water clusters.
citing papers explorer
-
Low-rank compression of two-electron reduced density matrices
A structure-preserving low-rank factorization of 2RDMs achieves linear effective rank scaling with ~99% compression for octane while retaining chemical accuracy and enabling quadratic-memory interpolation in ab initio workflows.
-
Accurate, full-dimensional computations of thousands of complex vibrational eigenstates with tree tensor network states
Tree tensor network states combined with DMRG allow accurate full-dimensional computations of thousands of vibrational eigenstates for molecules ranging from small benchmarks to 33-dimensional protonated water clusters.