Transition Path Theory from Biased Simulations

Abstract

Transition Path Theory (TPT) provides a rigorous framework to investigate the dynamics of rare thermally activated transitions. In this theory, a central role is played by the forward committor function q^+(x), which provides the ideal reaction coordinate. Furthermore, the reactive dynamics and kinetics are fully characterized in terms of two time-independent scalar and vector distributions. In this work, we develop a scheme which enables all these ingredients of TPT to be efficiently computed using the short non-equilibrium trajectories generated by means of a specific combination of enhanced path sampling techniques. In particular, first, we further extend the recently introduced Self-Consistent Path Sampling (SCPS) algorithm in order to compute the committor q^+(x). Next, we show how this result can be exploited in order to define efficient algorithms which enable us to directly sample the transition path ensemble.

arXiv commentVersion accepted for publication in J. Chem. Phys

References in corpus (9)

• A Novel Path Sampling Method for the Calculation of Rate Constants
• From Metadynamics to Dynamics
• Forward Flux Sampling for rare event simulations
• Dominant Pathways in Protein Folding
• Quantitative Protein Dynamics from Dominant Folding Pathways
• Generating Transition Paths by Langevin Bridges
• Flows in Complex Networks: Theory, Algorithms, and Application to Lennard-Jones Cluster Rearrangement
• All-atom simulations reveal how single point mutations promote serpin misfolding
• Fluctuations in the Ensemble of Reaction Pathways

Cited by in corpus (4)

• Reinforcement learning of rare diffusive dynamics
• Optimal navigation strategy of active Brownian particles in target-search problems
• Sampling a rare protein transition with a hybrid classical-quantum computing algorithm
• Transition-path sampling for Run-and-Tumble particles