Gaussian process models of potential energy surfaces with boundary optimization

Broad, Jack; Preston, Simon; Wheatley, Richard J.; Graham, Richard S.

Abstract

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at a long range, and the crossover distance between this model and the Gaussian process is learnt from the training data. The results are presented for different implementations of this procedure, known as boundary optimization, across the following dimer systems: CO-Ne, HF-Ne, HF-Na+, CO2-Ne, and (CO2)2. The technique reduces the number of training points, at fixed accuracy, by up to ∼49%, compared to our previous work based on a sequential learning technique. The approach is readily transferable to other statistical methods of prediction or modeling problems.

Citation

Broad, J., Preston, S., Wheatley, R. J., & Graham, R. S. (2021). Gaussian process models of potential energy surfaces with boundary optimization. Journal of Chemical Physics, 155(14), Article 144106. https://doi.org/10.1063/5.0063534

• Journal Article Type: Article
• Acceptance Date: Sep 29, 2021
• Online Publication Date: Oct 13, 2021
• Publication Date: Oct 14, 2021
• Deposit Date: Oct 14, 2021
• Publicly Available Date: Oct 15, 2021
• Journal: Journal of Chemical Physics
• Print ISSN: 0021-9606
• Electronic ISSN: 1089-7690
• Publisher: American Institute of Physics
• Peer Reviewed: Peer Reviewed
• Volume: 155
• Issue: 14
• Article Number: 144106
• DOI: https://doi.org/10.1063/5.0063534
• Keywords: Physical and Theoretical Chemistry; General Physics and Astronomy
• Public URL: https://nottingham-repository.worktribe.com/output/6459215
• Publisher URL: https://aip.scitation.org/doi/10.1063/5.0063534
• Additional Information: This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Jack Broad, Simon Preston, Richard J. Wheatley, and Richard S. Graham; , "Gaussian process models of potential energy surfaces with boundary optimization", J. Chem. Phys. 155, 144106 (2021) and may be found at https://doi.org/10.1063/5.0063534