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Software News and Update MOLCAS 7: The Next Generation

Abstract : Some of the new unique features of the MOLCAS quantum chemistry package version 7 are presented inthis report. In particular, the Cholesky decomposition method applied to some quantum chemical methods is described. This approach is used both in the context of a straight forward approximation of the two-electron integrals and in the generation of so-called auxiliary basis sets. The article describes how the method is implemented for most known wave functions models: self-consistent field, density functional theory, 2nd order perturbation theory, complete-active space self-consistent field multiconfigurational reference 2nd order perturbation theory, and coupled-cluster methods. The report further elaborates on the implementation of a restricted-active space self-consistent field reference function in conjunction with 2nd order perturbation theory. The average atomic natural orbital basis for relativistic calculations, covering the whole periodic table, are described and associated unique properties are demonstrated. Furthermore, the use of the arbitrary order Douglas-Kroll-Hess transformation for one-component relativistic calculations and its implementation are discussed. This section especially focuses on the implementation of the so-called picture-change-free atomic orbital property integrals. Moreover, the ElectroStatic Potential Fitted scheme, a version of a quantum mechanics/molecular mechanics hybrid method implemented in MOLCAS, is described and discussed. Finally, the report discusses the use of the MOLCAS package for advanced studies of photo chemical phenomena and the usefulness of the algorithms for constrained geometry optimization in MOLCAS in association with such studies. (c) 2009 Wiley Periodicals, Inc. J Corn put Chem 31: 224-247, 2010
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Submitted on : Tuesday, February 7, 2017 - 4:17:03 PM
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Francesco Aquilante, Luca de Vico, Nicolas Ferré, Giovanni Ghigo, Per-Åke Malmqvist, et al.. Software News and Update MOLCAS 7: The Next Generation. Journal of Computational Chemistry, Wiley, 2010, 31 (1), pp.224--247. ⟨10.1002/jcc.21318⟩. ⟨hal-01460198⟩



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