The performance of minima hopping and evolutionary algorithms for cluster structure prediction

Schönborn, Sandro E. and Goedecker, Stefan and Roy, Shantanu and Oganov, Artem R.. (2009) The performance of minima hopping and evolutionary algorithms for cluster structure prediction. Journal of Chemical Physics, 130 (14). p. 144108.

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Official URL: https://edoc.unibas.ch/76321/

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We compare evolutionary algorithms with minima hopping for global optimization in the field of cluster structure prediction. We introduce a new average offspring recombination operator and compare it with previously used operators. Minima hopping is improved with a softening method and a stronger feedback mechanism. Test systems are atomic clusters with Lennard-Jones interaction as well as silicon and gold clusters described by force fields. The improved minima hopping is found to be well-suited to all these homoatomic problems. The evolutionary algorithm is more efficient for systems with compact and symmetric ground states, including LJ(150), but it fails for systems with very complex energy landscapes and asymmetric ground states, such as LJ(75) and silicon clusters with more than 30 atoms. Both successes and failures of the evolutionary algorithm suggest ways for its improvement.
Faculties and Departments:05 Faculty of Science > Departement Physik > Physik > Physik (Goedecker)
UniBasel Contributors:Goedecker, Stefan
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:AIP Publishing
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:22 Apr 2020 07:58
Deposited On:22 Apr 2020 07:58

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