Alchemical and structural distribution based representation for improved QML
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4495967
Author(s) Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole
Author(s) at UniBasel von Lilienfeld, Anatole
Huang, Bing
Christensen, Anders Steen
Year 2018
Year: comment 2018
Title Alchemical and structural distribution based representation for improved QML
Journal Journal of Chemical Physics
Volume 148
Number 24
Pages / Article-Number 241717
Abstract We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)(40)-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency
Publisher AIP Publishing
ISSN/ISBN 0021-9606 ; 1089-7690
URL arXiv:1712.08417
edoc-URL https://edoc.unibas.ch/68690/
Full Text on edoc No
Digital Object Identifier DOI 10.1063/1.5020710
ISI-Number 000437190300020
 
   

MCSS v5.8 PRO. 0.439 sec, queries - 0.000 sec ©Universität Basel  |  Impressum   |    
08/08/2020