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Cited by 188

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N-Electron Valence State Perturbation Theory Based on a Density Matrix Renormalization Group Reference Function, with Applications to the Chromium Dimer and a Trimer Model of Poly(p-Phenylenevinylene)

Open access
Guo, Sheng, Watson, Mark A., Hu, Weifeng, Sun, Qiming, Chan, Garnet Kin-Lic·2016·Journal of Chemical Theory and Computation

Abstract

The strongly contracted variant of second-order N-electron valence state perturbation theory (NEVPT2) is an efficient perturbative method to treat dynamic correlation without the problems of intruder states or level shifts, while the density matrix renormalization group (DMRG) provides the capability to address static correlation in large active spaces. We present a combination of the DMRG and strongly contracted NEVPT2 (DMRG-SC-NEVPT2) that uses an efficient algorithm to compute high-order reduced-density matrices from DMRG wave functions. The capabilities of DMRG-SC-NEVPT2 are demonstrated on calculations of the chromium dimer potential energy curve at the basis set limit, and the excitation energies of a trimer model of poly(p-phenylenevinylene) (PPV(n = 3)).

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Metadata

Authors
Guo, S., Watson, M. A., Hu, W., Sun, Q., & Chan, G. K.-L.
Venue
Journal of Chemical Theory and Computation
Published
2016-03-04
Volume
12
Issue
4
Pages
1583-1591
ISSN
  • 1549-9618 (ISSN-L)
  • 1549-9626
OpenAlex
W2279035142
Cited by
188
References
6
FWCI
12.07
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: N-Electron Valence State Perturbation Theory Based on a Density Matrix Renormalization Group Reference Function, with Applications to the Chromium Dimer and a Trimer Model of Poly(p-Phenylenevinylene). https://app.cochat.ai/papers/10.1021/acs.jctc.5b01225
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Guo, S., Watson, M. A., Hu, W., Sun, Q., & Chan, G. K.-L. (2016). N-Electron Valence State Perturbation Theory Based on a Density Matrix Renormalization Group Reference Function, with Applications to the Chromium Dimer and a Trimer Model of Poly(p-Phenylenevinylene). Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.5b01225

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