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Global Elucidation of Self-Consistent Field Solution Space Using Basin Hopping

  • Xinju Dong
  • , Andrew D. Mahler
  • , Emily M. Kempfer-Robertson
  • , Lee M. Thompson

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Reliable global elucidation of (subsets of) self-consistent field solutions is required for continued development and application of computational approaches that utilize these solutions as reference wavefunctions. We report the derivation and implementation of a stochastic approach to perform global elucidation of self-consistent field solutions by exploiting the connection between global optimization and global elucidation problems. We discuss the design of the algorithm through combining basin-hopping search algorithms with a Lie algebraic approach to linearize self-consistent field solution space, while also allowing preservation of desired spin-symmetry properties of the wavefunction. The performance of the algorithm is demonstrated on minimal basis C2v H4 due to its use as a model system for global self-consistent field solution exploration algorithms. Subsequently, we show that the model is capable of successfully identifying low-lying self-consistent solutions of benzene and NO2 with polarized double-zeta and triple-zeta basis sets and examine the properties of these solutions.

Original languageEnglish
Pages (from-to)5635-5644
Number of pages10
JournalJournal of Chemical Theory and Computation
Volume16
Issue number9
DOIs
StatePublished - Sep 8 2020
Externally publishedYes

Funding

The authors gratefully acknowledge financial support from the ACS Petroleum Research Fund (ACS-PRF no. 59768-DNI6), the University of Louisville and an EVPRI Internal Research Grant from the Office of the Executive Vice President for Research and Innovation. E.M.K.-R. and X.D. would like to acknowledge funding from the University of Louisville University Fellowship award. This work was conducted in part using the resources of the University of Louisville's research computing group and the Cardinal Research Cluster. The authors gratefully acknowledge financial support from the ACS Petroleum Research Fund (ACS-PRF no. 59768-DNI6), the University of Louisville and an EVPRI Internal Research Grant from the Office of the Executive Vice President for Research and Innovation. E.M.K.-R. and X.D. would like to acknowledge funding from the University of Louisville University Fellowship award. This work was conducted in part using the resources of the University of Louisville’s research computing group and the Cardinal Research Cluster.

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