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Deep Learning Platform for Molecular Simulations

Speaker

Han Wang, Institute of Applied Physics and Computational Mathematics

Time

2018.05.11 10:00-11:00

Venue

601, Pao Yue-Kong Library

Abstract

We introduce a series of deep learning based methods for molecular simulations at different scales: 1) the Deep Potential Molecular Dynamics (DeePMD): a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data; 2) Deep Coarse-Grained Potential (DeePCG): generalization of DeePMD to the context of coarse graining; 3) Reinforced Dynamics: to use many collective variables for enhanced sampling and free energy calculation. In particular, we introduce the platform, the DeePMD-kit package, that we developed for wide applications in computational physics, chemistry, biology, and materials science.