PyRETIS 3: Conquering rare and slow events without boundaries

• Published in: Journal of computational chemistry Vol. 45; no. 15; pp. 1224 - 1234
• Main Authors: Vervust, Wouter, Zhang, Daniel T, Ghysels, An, Roet, Sander, van Erp, Titus S, Riccardi, Enrico
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 05-06-2024
• Subjects: Algorithms; Clustering; Computer simulation; Machine learning; Metastable state; Modular structures; Sampling; path sampling; PyRETIS; rare event; kinetics; slow event; Python
• ISSN: 0192-8651; 1096-987X
• DOI: 10.1002/jcc.27319

We present and discuss the advancements made in PyRETIS 3, the third instalment of our Python library for an efficient and user-friendly rare event simulation, focused to execute molecular simulations with replica exchange transition interface sampling (RETIS) and its variations. Apart from a general rewiring of the internal code towards a more modular structure, several recently developed sampling strategies have been implemented. These include recently developed Monte Carlo moves to increase path decorrelation and convergence rate, and new ensemble definitions to handle the challenges of long-lived metastable states and transitions with unbounded reactant and product states. Additionally, the post-analysis software PyVisa is now embedded in the main code, allowing fast use of machine-learning algorithms for clustering and visualising collective variables in the simulation data.