Berlin 2018 – wissenschaftliches Programm

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SYMS: Symposium Data-driven Methods in Molecular Simulations of Soft-Matter Systems

SYMS 1: Data-driven Methods in Molecular Simulations of Soft-Matter Systems

SYMS 1.3: Hauptvortrag

Montag, 12. März 2018, 16:00–16:30, H 0105

Girsanov reweighting for path ensembles and Markov state models — •Bettina G. Keller1, Luca Donati1, and Carsten Hartmann21Freie Universität Berlin, Germany — 2Brandenburgische Technische Universität Cottbus-Senftenberg, Germany

Enhanced sampling techniques, such as metadynamics or umbrella sampling, in which a biasing potential U(x) is added to the unbiased force field V(x) increase the sampling of rare events. However, the distortion of the timescales in the system due to the biasing potential is not uniform. The resulting biased trajectories can hence not be used to estimate models of the molecular dynamics, e.g. Markov state models.

I will present the Girsanov reweighting method with which one can estimate the the expected path ensemble average of an unbiased dynamics for a set of biased paths. The method is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models of molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight these models by combining it with a reweighting of the Boltzmann distribution. Besides its use in enhanced sampling simulations, the Girsanov reweighting can also be used to test the response of the slow dynamic processes to perturbations of the potential energy surface.

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