Automatic Partition of Orbital Spaces Based on Singular Value Decomposition in the Context of Embedding Theories
Author(s) -
Daniel Claudino,
Nicholas J. Mayhall
Publication year - 2019
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.8b01112
Subject(s) - embedding , singular value decomposition , partition (number theory) , context (archaeology) , decomposition , computer science , theoretical computer science , value (mathematics) , mathematics , algorithm , artificial intelligence , chemistry , combinatorics , machine learning , geography , archaeology , organic chemistry
We present a simple approach for orbital space partitioning to be employed in the projection-based embedding theory developed by Goodpaster and co-workers [ Manby et al. J. Chem. Theory Comput. 2012 , 8 , 2564 ]. Once the atoms are assigned to the desired subspaces, the molecular orbitals are projected onto the atomic orbitals centered on active atoms and then singular value decomposed. The right singular vectors are used to rotate the initial molecular orbitals, taking the largest gap in the singular values spectrum to define the most suitable partition of the occupied orbital space. This scheme is free from numerical parameters, contrary to the Mulliken charge threshold or the completeness criterion previously used. The performance of this new prescription is assessed in a test set of several distinct reactions, the deprotonation of decanoic acid, the Diels-Alder reaction of 1,3-butadiene and octadecanonaene, the torsional potential of a retinal derivative, and the critical points along the reaction coordinate of an example of the Menshutkin S N 2 reaction inside a carbon nanotube.
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