PyRETIS 3: Conquering rare and slow events without boundaries

Wouter Vervust, Daniel T. Zhang, An Ghysels, Sander Roet, Titus S. van Erp, Enrico Riccardi*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)1224-1234
Number of pages11
JournalJournal of Computational Chemistry
Volume45
Issue number15
Early online date12 Feb 2024
DOIs
Publication statusPublished - 5 Jun 2024

Bibliographical note

Publisher Copyright:
© 2024 Wiley Periodicals LLC.

Funding

We acknowledge funding support from the Research Council of Norway for the 'Theolight' toppforsk project (Grant No. 275506). We also acknowledge funding of the FWO (project G002520N and project G094023N), BOF of Ghent University and the European Union (ERC Consolidator grant, 101086145 PASTIME).

FundersFunder number
European Commission
European Research Council101086145 PASTIME
European Research Council
Fonds Wetenschappelijk OnderzoekG002520N, G094023N
Fonds Wetenschappelijk Onderzoek
Universiteit Gent
Norges Forskningsråd275506
Norges Forskningsråd

    Keywords

    • PyRETIS
    • Python
    • kinetics
    • path sampling
    • rare event
    • slow event

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