The End of Ab Initio MD
- TH Department Online Seminar
- Date: Jun 30, 2022
- Time: 11:00 AM (Local Time Germany)
- Speaker: Prof. Gábor Csányi
- University of Cambridge, Department of Engineering, Cambridge, United Kingdom
- Location: https://zoom.us/j/91272966563?pwd=eGo0V2Mrd3pwOXVaVXJ0VklGd041QT09
- Room: Meeting ID: 912 7296 6563 | Passcode: 057467
- Host: TH Department

The resulting potentials are reactive, many-body, reach accuracies of a
few meV/atom, with evaluation costs that are on the order of 1-10
ms/atom/cpucore. Applications to diverse material systems are being
published every week, and the extension to molecular force fields is
well underway. Important challenges remain: treatment of long range
interactions in the form of charge self-consistency, magnetism etc. On
the methodological side, with deeper understanding of the geometry
problem of describing environments comes what appears to be a
convergence between various modeling approaches (neural networks,
kernels, polynomials). Protocols of putting together the training data
are being explored, including "active learning". I am particularly
interested in the amount physics and chemistry "knowledge" that we can
impute into these approximations, and that they can be used to help
"extrapolate" correctly into regions of configuration space far from
those in the data set.