BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces
Shane Carr, Roman Garnett, Cynthia Lo
Abstract
We present a novel application of Bayesian optimization to the field of surface science: rapidly and accurately searching for the global minimum on potential energy surfaces. Controlling molecule-surface interactions is key for applications ranging from environmental catalysis to gas sensing. We present pragmatic techniques, including exploration/exploitation scheduling and a custom covariance kernel that encodes the properties of our objective function. Our method, the Bayesian Active Site Calculator (BASC), outperforms differential evolution and constrained minima hopping – two state-of-the-art approaches – in trial examples of carbon monoxide adsorption on a hematite substrate, both with and without a defect.
BibTeX
@InProceedings{pmlr-v48-carr16,
title = {BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces},
author = {Carr, Shane and Garnett, Roman and Lo, Cynthia},
booktitle = {Proceedings of The 33rd International Conference on Machine Learning},
pages = {898--907},
year = {2016},
editor = {Balcan, Maria Florina and Weinberger, Kilian Q.},
volume = {48},
series = {Proceedings of Machine Learning Research},
address = {New York, New York, USA},
month = {20--22 Jun},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v48/carr16.pdf},
url = {https://proceedings.mlr.press/v48/carr16.html},
abstract = {We present a novel application of Bayesian optimization to the field of surface science: rapidly and accurately searching for the global minimum on potential energy surfaces. Controlling molecule-surface interactions is key for applications ranging from environmental catalysis to gas sensing. We present pragmatic techniques, including exploration/exploitation scheduling and a custom covariance kernel that encodes the properties of our objective function. Our method, the Bayesian Active Site Calculator (BASC), outperforms differential evolution and constrained minima hopping – two state-of-the-art approaches – in trial examples of carbon monoxide adsorption on a hematite substrate, both with and without a defect.}
}