Distilled non-conservative force models in a multi-time-step integrator accelerate neural-network-potential molecular dynamics by up to 5.6x on tested systems without degrading sampling accuracy.
A Stochastic, Resonance-Free Multiple Time-Step Algorithm for Polarizable Models That Permits Very Large Time Steps
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Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces
Distilled non-conservative force models in a multi-time-step integrator accelerate neural-network-potential molecular dynamics by up to 5.6x on tested systems without degrading sampling accuracy.