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Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:

王涵 副研究员, 北京应用物理与计算数学研究所

Inviter: 黄记祖
Title:
Deep Potential Molecular dynamics: a scalable model with the accuracy of quantum mechanics
Time & Venue:
2017.11.7 16:30-18:30 Z301
Abstract:
We introduce a new scheme for molecular simulations, based on a many-body potential and interatomic forces generated by a deep neural network trained with ab initio data. We show that the proposed scheme, which we call Deep Potential Molecular Dynamics (DeePMD), provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DeePMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size. Moreover, in a few test cases, DeePMD shows good structural transferability to thermodynamic conditions not included in the original training data.
 

 

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