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Cited by 425

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Coupled-cluster methods including noniterative corrections for quadruple excitations

Bomble, Yannick J., Stanton, John F., Kállay, Mihály, Gauss, Jürgen·2005·The Journal of Chemical Physics

Abstract

A new method is presented for treating the effects of quadruple excitations in coupled-cluster theory. In the approach, quadruple excitation contributions are computed from a formula based on a non-Hermitian perturbation theory analogous to that used previously to justify the usual noniterative triples correction used in the coupled cluster singles and doubles method with a perturbative treatment of the triple excitations (CCSD(T)). The method discussed in this paper plays a parallel role in improving energies obtained with the full coupled-cluster singles, doubles, and triples method (CCSDT) by adding a perturbative treatment of the quadruple excitations (CCSDT(Q)). The method is tested for an extensive set of examples, and is shown to provide total energies that compare favorably with those obtained with the full singles, doubles, triples, and quadruples (CCSDTQ) method.

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Metadata

Authors
Bomble, Y. J., Stanton, J. F., Kállay, M., & Gauss, J.
Venue
The Journal of Chemical Physics
Published
2005-08-01
Volume
123
Issue
5
Pages
054101-054101
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2017245598
Cited by
425
References
35
FWCI
6.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Coupled-cluster methods including noniterative corrections for quadruple excitations. https://app.cochat.ai/papers/10.1063/1.1950567
The paper
Bomble, Y. J., Stanton, J. F., Kállay, M., & Gauss, J. (2005). Coupled-cluster methods including noniterative corrections for quadruple excitations. The Journal of Chemical Physics. https://doi.org/10.1063/1.1950567

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.