Have You Tried Turning It Off and On Again? Stochastic Resetting for Enhanced Sampling

O Blumer and B Hirshberg, WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE, 15, e70038 (2025).

DOI: 10.1002/wcms.70038

Molecular dynamics simulations are widely used across chemistry, physics, and biology, providing quantitative insight into complex processes with atomic detail. However, their limited timescale of a few microseconds is a significant obstacle in describing phenomena such as conformational transitions of biomolecules and polymorphism in molecular crystals. Recently, stochastic resetting, that is, randomly stopping and restarting the simulations, emerged as a powerful enhanced sampling approach, which is collective variable-free, highly parallelized, and easily implemented in existing molecular dynamics codes. Resetting expedites sampling rare events while enabling the inference of kinetic observables of the underlying process. It can be employed as a standalone tool or in combination with other enhanced sampling methods, such as Metadynamics, with each technique compensating for the drawbacks of the other. Here, we comprehensively describe resetting and its theoretical background, review recent developments in stochastic resetting for enhanced sampling, and provide instructive guidelines for practitioners.This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Theoretical and Physical Chemistry > Statistical Mechanics

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