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Systematic truncation of the virtual space in multiconfigurational perturbation theory

Aquilante, Francesco; Todorova, Tanya Kumanova; Gagliardi, Laura; Pedersen, Thomas LU and Roos, Björn LU (2009) In Journal of Chemical Physics 131(3).
Abstract
A method is suggested which allows truncation of the virtual space in Cholesky decomposition-based multiconfigurational perturbation theory (CD-CASPT2) calculations with systematic improvability of the results. The method is based on a modified version of the frozen natural orbital (FNO) approach used in coupled cluster theory. The idea is to exploit the near-linear dependence among the eigenvectors of the virtual-virtual block of the second-order Moller-Plesset density matrix. It is shown that FNO-CASPT2 recovers more than 95% of the full CD-CASPT2 correlation energy while requiring only a fraction of the total virtual space, especially when large atomic orbital basis sets are in use. Tests on various properties commonly investigated with... (More)
A method is suggested which allows truncation of the virtual space in Cholesky decomposition-based multiconfigurational perturbation theory (CD-CASPT2) calculations with systematic improvability of the results. The method is based on a modified version of the frozen natural orbital (FNO) approach used in coupled cluster theory. The idea is to exploit the near-linear dependence among the eigenvectors of the virtual-virtual block of the second-order Moller-Plesset density matrix. It is shown that FNO-CASPT2 recovers more than 95% of the full CD-CASPT2 correlation energy while requiring only a fraction of the total virtual space, especially when large atomic orbital basis sets are in use. Tests on various properties commonly investigated with CASPT2 demonstrate the reliability of the approach and the associated reduction in computational cost and storage demand of the calculations. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
decomposition, matrix, coupled cluster calculations, eigenvalues and eigenfunctions, physics computing, perturbation theory
in
Journal of Chemical Physics
volume
131
issue
3
publisher
American Institute of Physics
external identifiers
  • wos:000268206800019
  • scopus:67651213466
ISSN
0021-9606
DOI
10.1063/1.3157463
language
English
LU publication?
yes
id
11e95a58-bc95-4a05-b84d-90e8ce9fc374 (old id 1461539)
date added to LUP
2009-08-24 10:49:56
date last changed
2017-09-17 04:33:34
@article{11e95a58-bc95-4a05-b84d-90e8ce9fc374,
  abstract     = {A method is suggested which allows truncation of the virtual space in Cholesky decomposition-based multiconfigurational perturbation theory (CD-CASPT2) calculations with systematic improvability of the results. The method is based on a modified version of the frozen natural orbital (FNO) approach used in coupled cluster theory. The idea is to exploit the near-linear dependence among the eigenvectors of the virtual-virtual block of the second-order Moller-Plesset density matrix. It is shown that FNO-CASPT2 recovers more than 95% of the full CD-CASPT2 correlation energy while requiring only a fraction of the total virtual space, especially when large atomic orbital basis sets are in use. Tests on various properties commonly investigated with CASPT2 demonstrate the reliability of the approach and the associated reduction in computational cost and storage demand of the calculations.},
  author       = {Aquilante, Francesco and Todorova, Tanya Kumanova and Gagliardi, Laura and Pedersen, Thomas and Roos, Björn},
  issn         = {0021-9606},
  keyword      = {decomposition,matrix,coupled cluster calculations,eigenvalues and eigenfunctions,physics computing,perturbation theory},
  language     = {eng},
  number       = {3},
  publisher    = {American Institute of Physics},
  series       = {Journal of Chemical Physics},
  title        = {Systematic truncation of the virtual space in multiconfigurational perturbation theory},
  url          = {http://dx.doi.org/10.1063/1.3157463},
  volume       = {131},
  year         = {2009},
}