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Reducing search time for optimal geometry of small molecular clusters
Author(s) -
Steen Kay J.,
Smith Lars Erik
Publication year - 2002
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/qua.10024
Subject(s) - hypersurface , reduction (mathematics) , set (abstract data type) , energy minimization , point (geometry) , algorithm , quantum , energy (signal processing) , work (physics) , mathematics , geometry , mathematical optimization , computer science , physics , computational chemistry , chemistry , quantum mechanics , mathematical analysis , statistics , programming language
This work has developed and tested an optimal geometry search algorithm. The results shows that response modeling of the energy hypersurface reduce the number of single‐point calculations needed to find the optimal geometry. In large systems it seems to reduce the number of necessary points by 50% or more. The method is based on an updating partial least‐squares regression (PLSR) algorithm for choosing a set of candidate configurations by minimizing the predicted response. Since the PLSR modeling time is short, compared to the quantum chemical calculations, the search time is reduced by approximately the same percentage as the reduction in number of single‐point calculations needed. © 2002 John Wiley & Sons, Inc. Int J Quantum Chem, 2002