Analysis of the Adaptive Multilevel Splitting method on the isomerization of alanine dipeptide

TL;DR

This paper applies the Adaptive Multilevel Splitting method to study the isomerization of alanine dipeptide, demonstrating its effectiveness in estimating transition probabilities, times, and the committor function.

Contribution

It introduces the application of the Adaptive Multilevel Splitting method to alanine dipeptide isomerization, highlighting its unbiasedness, robustness, and utility in computing transition properties.

Findings

Unbiased probability estimation demonstrated.

Method is robust to reaction coordinate choice.

Transition times and committor functions can be approximated.

Abstract

We apply the Adaptive Multilevel Splitting method to the Ceq -> Cax transition of alanine dipeptide in vacuum. Some properties of the algorithm are numerically illustrated, such as the unbiasedness of the probability estimator and the robustness of the method with respect to the choice of the reaction coordinate. We also calculate the transition time obtained via the probability estimator, using an appropriate ensemble of initial conditions. Finally, we show how the Adaptive Multilevel Splitting method can be used to compute an approximation of the committor function.