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Monday, July 08, 2019

Simulating Molecular Motion with Neural Networks

Have now seen several examples of using neural nets to simulate complex systems by generating a model from data.    Thought provoking example I am following up on.

Researchers Cast Neural Nets to Simulate Molecular Motion 
Los Alamos National Laboratory News
By Nancy Ambrosiano      July 2, 2019

The U.S. Department of Energy's Los Alamos National Laboratory (LANL), the University of North Carolina at Chapel Hill, and the University of Florida demonstrated that artificial neural nets can be taught to encode quantum mechanical laws that define molecular motion, potentially advancing simulations across many disciplines. Said LANL's Justin Smith, "We can now model materials and molecular dynamics billions of times faster compared to conventional quantum methods, while retaining the same level of accuracy." The researchers developed a machine learning technique to build empirical potentials—atomic dynamics descriptions that follow classical physical and Newtonian laws—from data collected about millions of compounds. The transfer learning technique can be applied to new molecules in milliseconds .... " 

Researchers cast neural nets to simulate molecular motion
Machine learning allows quantum mechanics to be efficiently applied to molecular simulations for drug development, detonation physics and more .... " 

Publication:   J. S. Smith, B. T. Nebgen, R. Zubatyuk, N. Lubbers, C. Devereux, K. Barros, S. Tretiak, O. Isayev, A. E. Roitberg, “Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning,” Nature Communications 10.1038/s41467-019-10827-4 (2019)  ..... " 

Technical paper:  https://www.nature.com/articles/s41467-019-10827-4

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