Modeling coarse-grained lattice dynamics with ab initio generalized Langevin equation

ORAL

Abstract

We model the dynamics of coarse-grained variables defined on Bravais lattice with multi-dimensional ab initio generalized Langevin equation (AIGLE). The memory kernel and the noise generator in AIGLE are learned from molecular dynamics (MD) data and constrained by the fluctuation-dissipation theorem.



We demonstrate the approach with a study of the ferroelectric crystal lead titanate. We introduce a local kernel approximation and train an infinite-dimensional AIGLE to model the dynamics of interacting local dipole moments on a coarse-grained lattice. AIGLE is shown to be consistent with MD data not only for the autocorrelation of local dipole moments and global polarization, but also for the cross-correlation between neighboring local dipoles.

* This work was supported by the Computational Chemical Center: Chemistry in Solution and at Interfaces (CSI) funded by the DOE Award DE-SC0019394. The simulations in this work were performed on computational resources managed and supported by Princeton Research Computing, a consortium of groups including the Princeton Institute for Computational Science and Engineering (PICSciE) and the Office of Information Technology's High Performance Computing Center and Visualization Laboratory at Princeton University.

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Publication: Xie, P., Car, R. and E, W., Ab Initio Generalized Langevin Equation. (Under Review)

Presenters

  • Pinchen Xie

    Princeton University

Authors

  • Pinchen Xie

    Princeton University

  • Roberto Car

    Princeton University

  • Weinan E

    AI for Science Institute, Beijing