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Constrained numerical gradients and composite gradients: Practical tools for geometry optimization and potential energy surface navigation
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.
2015 (English)In: Journal of Computational Chemistry, ISSN 0192-8651, E-ISSN 1096-987X, Vol. 36, no 22, 1698-1708 p.Article in journal (Refereed) Published
Abstract [en]

A method is proposed to easily reduce the number of energy evaluations required to compute numerical gradients when constraints are imposed on the system, especially in connection with rigid fragment optimization. The method is based on the separation of the coordinate space into a constrained and an unconstrained space, and the numerical differentiation is done exclusively in the unconstrained space. The decrease in the number of energy calculations can be very important if the system is significantly constrained. The performance of the method is tested on systems that can be considered as composed of several rigid groups or molecules, and the results show that the error with respect to conventional optimizations is of the order of the convergence criteria. Comparison with another method designed for rigid fragment optimization proves the present method to be competitive. The proposed method can also be applied to combine numerical and analytical gradients computed at different theory levels, allowing an unconstrained optimization with numerical differentiation restricted to the most significant degrees of freedom. This approach can be a practical alternative when analytical gradients are not available at the desired computational level and full numerical differentiation is not affordable. (c) 2015 Wiley Periodicals, Inc.

Place, publisher, year, edition, pages
2015. Vol. 36, no 22, 1698-1708 p.
Keyword [en]
numerical gradients, constrained geometry optimization, MOLCAS
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-260597DOI: 10.1002/jcc.23987ISI: 000358085400006PubMedID: 26140702OAI: oai:DiVA.org:uu-260597DiVA: diva2:848527
Funder
eSSENCE - An eScience CollaborationSwedish Research Council
Available from: 2015-08-25 Created: 2015-08-21 Last updated: 2017-12-04Bibliographically approved

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Lindh, RolandGalvan, Ignacio Fdez.

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