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arxiv: 1409.4992 · v1 · pith:52KT5RCGnew · submitted 2014-09-17 · ⚛️ physics.chem-ph · cs.NA

An adaptive mass algorithm for Car-Parrinello and Ehrenfest ab initio molecular dynamics

classification ⚛️ physics.chem-ph cs.NA
keywords car-parrinellodynamicsmolecularehrenfestmassartificialadaptivealgorithm
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Ehrenfest and Car-Parrinello molecular dynamics are computational alternatives to approximate Born-Oppenheimer molecular dynamics without solving the electron eigenvalue problem at each time-step. A non-trivial issue is to choose the artificial electron mass parameter appearing in the Car-Parrinello method to achieve both good accuracy and high computational efficiency. In this paper, we propose an algorithm, motivated by the Landau-Zener probability, to systematically choose an artificial mass dynamically, which makes the Car-Parrinello and Ehrenfest molecular dynamics methods dependent only on the problem data. Numerical experiments for simple model problems show that the time-dependent adaptive artificial mass parameter improves the efficiency of the Car-Parrinello and Ehrenfest molecular dynamics.

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