Application of Clustering Algorithms to Partitioning Configuration Space in Fitting Reactive Potential Energy Surfaces
A large number of energy points add great difficulty to construct reactive potential energy surfaces (PES). To alleviate this, exemplar-based clustering is applied to partition the configuration space into several smaller parts. The PES of each part can be constructed easily and the global PES is ob...
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| Vydané v: | The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment, & general theory Ročník 122; číslo 12; s. 3140 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
29.03.2018
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| ISSN: | 1520-5215, 1520-5215 |
| On-line prístup: | Zistit podrobnosti o prístupe |
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| Shrnutí: | A large number of energy points add great difficulty to construct reactive potential energy surfaces (PES). To alleviate this, exemplar-based clustering is applied to partition the configuration space into several smaller parts. The PES of each part can be constructed easily and the global PES is obtained by connecting all of the PESs of small parts. This divide and conquer strategy is first demonstrated in the fitting of PES for OH
with Gaussian process regression (GPR) and further applied to construct PESs for CH
and O+CH
with artificial neural networks (NN). The accuracy of PESs is tested by fitting errors and direct comparisons with previous PESs in dynamically important regions. As for OH
and CH
, quantum scattering calculations further validate the global accuracy of newly fitted PESs. The results suggest that partitioning the configuration space by clustering provides a simple and useful method for the construction of PESs for systems that require a large number of energy points. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1520-5215 1520-5215 |
| DOI: | 10.1021/acs.jpca.8b00859 |