Gaussian Approximation Potentials: a brief tutorial introduction

Albert P. Bartók; Gábor Csányi

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arXiv · 1502.01366

Gaussian Approximation Potentials: a brief tutorial introduction

Albert P. Bartók·Gábor Csányi

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Abstract

We present a swift walk-through of our recent work that uses machine learning to fit interatomic potentials based on quantum mechanical data. We describe our Gaussian Approximation Potentials (GAP) framework, discussing a variety of descriptors, how to train the model on total energies and derivatives and the simultaneous use of multiple models. We also show a small example using QUIP, the software sandbox implementation of GAP that is available for non-commercial use.

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Albert P. Bartók, Gábor Csányi. 2015-02-04. Gaussian Approximation Potentials: a brief tutorial introduction. https://arxiv.org/abs/1502.01366

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