2023
DOI: 10.1021/acs.jctc.2c01316
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New Density Matrix Renormalization Group Approaches for Strongly Correlated Systems Coupled with Large Environments

Abstract: Thanks to the high compression of the matrix product state (MPS) form of the wave function and the efficient site-by-site iterative sweeping optimization algorithm, the density matrix normalization group (DMRG) and its time-dependent variant (TD-DMRG) have been established as powerful computational tools in accurately simulating the electronic structure and quantum dynamics of strongly correlated molecules with a large number (101–2) of quantum degrees of freedom (active orbitals or vibrational modes). However… Show more

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Cited by 4 publications
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“…The tensor network methods have gained great attention in the simulation of the nonadiabatic dynamics of complex systems due to their high accuracy and efficiency. In mathematical formula, the ML-MCTDH method also belongs to a kind of tree-structure tensor network . Another representative approach is the chain-like tensor network method, or so-called tensor train algorithm, in which the wave functions and operators are expressed in terms of the matrix product format, i.e.…”
Section: Introductionmentioning
confidence: 99%
“…The tensor network methods have gained great attention in the simulation of the nonadiabatic dynamics of complex systems due to their high accuracy and efficiency. In mathematical formula, the ML-MCTDH method also belongs to a kind of tree-structure tensor network . Another representative approach is the chain-like tensor network method, or so-called tensor train algorithm, in which the wave functions and operators are expressed in terms of the matrix product format, i.e.…”
Section: Introductionmentioning
confidence: 99%