Bulletin of the American Physical Society
APS March Meeting 2021
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session Y26: Predicting Rare Event Kinetics in Complex Systems with Theory, Simulations and Machine Learning IV
11:30 AM–2:30 PM,
Friday, March 19, 2021
Sponsoring Unit: DCP
Chair: Pratyush Tiwary, Univ of Maryland, College Park; Steffen Wolff, University of Freiburg
Abstract: Y26.00005 : Path probability ratios for Langevin dynamics – exact and approximate*
12:42 PM–1:18 PM
Most published path probability ratios are derived for overdamped Langevin dynamics. Yet, overdamped Langevin dynamics is rarely used in MD simulations. Instead a variety of integration schemes for Langevin dynamics are used. Simply applying the path probability ratio for overdamped Langevin dynamics to a Langevin trajectory introduces a sizeable error.
Here we derive the path probability ratio for the integration scheme of Langevin dynamics implemented in OpenMM. We demonstrate that it to accurately reweights Langevin trajectories.
By comparing this path probability ratio to the path probability ratio for overdamped Langevin dynamics, we then derive an approximate and general path probability ratio for Langevin dynamics. This approximate path probability ratio depends on the random number sequence used to generate the Langevin trajectory and on the bias potential. Because it is independent of the integration scheme, it removes requirement (b) and can be used as multi-purpose probability ratio for any Langevin trajectory. We show that the approximate path probability ratio yields highly accurate results, and discuss the limits of the approximation.
L Donati, BG Keller, J Chem Phys. 149, 072335 (2018)
S Kieninger, L Donati, BG Keller, Curr Opin Struct Biol, 61, 124-131 (2020)
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