PyVisA Visualization and Analysis of path sampling trajectories

PyVisA : Visualization and Analysis of path sampling trajectories

© 2020 Wiley Periodicals LLC.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 42(2021), 6 vom: 05. März, Seite 435-446
1. Verfasser: Aarøen, Ola (VerfasserIn)
Weitere Verfasser: Kiaer, Henrik, Riccardi, Enrico
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Journal Article Research Support, Non-U.S. Gov't PyRETIS PyVisA kinetics path sampling python rare event trimer water
Beschreibung
Zusammenfassung:© 2020 Wiley Periodicals LLC.
Rare event methods applied to molecular simulations are growing in popularity, accessible and customizable software solutions have thus been developed and released. One of the most recent is PyRETIS, an open Python library for performing path sampling simulations. Here, we introduce PyVisA, a postprocessing package for path sampling simulations, which includes visualization and analysis tools for interpreting path sampling outputs. PyVisA integrates PyRETIS functionalities and aims to facilitate the determination of: (a) the correlation of the order parameter with other descriptors; (b) the presence of latent variables; and (c) intermediate meta-stable states. To illustrate some of the main PyVisA features, we investigate the proton transfer reaction in a protonated water trimer simulated via a simple polarizable model (Stillinger-David)
Beschreibung:Date Completed 20.08.2021
Date Revised 20.08.2021
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1096-987X
DOI:10.1002/jcc.26467