Machine Learning-Based Nonadiabatic Dynamics Paper in JPCA!

M’s paper has been published in JPCA. This paper has been a long time coming and was one of the first things we started working on after joining Mizzou, so we are quite pleased to see its completion. In the paper, we introduce a simple modification of Wigner sampling for generating training data for machine learning-based nonadiabatic dynamics. As is hinted at in the conclusions, M is rapidly working on extending the method to electronic Hamiltonians and we hope to continue to expand and follow up on this study in the future. Link is here:

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