Complexity Reduction in Large Quantum Systems: Fragment Identification and Population Analysis via a Local Optimized Minimal Basis
PublisherAmerican Chemical Society
Rights accessOpen Access
European Commisision's projectMaX - Materials design at the eXascale (EC-H2020-676598)
EXTMOS - EXTended Model of Organic Semiconductors (EC-H2020-646176)
EoCoE - Energy oriented Centre of Excellence for computer applications (EC-H2020-676629)
We present, within Kohn–Sham density functional theory calculations, a quantitative method to identify and assess the partitioning of a large quantum-mechanical system into fragments. We then show how within this framework simple generalizations of other well-known population analyses can be used to extract, from first-principles, reliable electrostatic multipoles for the identified fragments. Our approach reduces arbitrariness in the fragmentation procedure and enables the possibility to assess quantitatively whether the corresponding fragment multipoles can be interpreted as observable quantities associated with a system moiety. By applying our formalism within the code BigDFT, we show that the use of a minimal set of in situ-optimized basis functions allows at the same time a proper fragment definition and an accurate description of the electronic structure.
CitationMohr, S. [et al.]. Complexity Reduction in Large Quantum Systems: Fragment Identification and Population Analysis via a Local Optimized Minimal Basis. "Journal of Chemical Theory and Computation", 21 Juliol 2017, vol. 13, núm. 9, p. 4079-4088.