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Automatic Clustering of Excited-State Trajectories: Application to Photoexcited Dynamics

[Image: see text] We introduce automatic clustering as a computationally efficient tool for classifying and interpreting trajectories from simulations of photo-excited dynamics. Trajectories are treated as time-series data, with the features for clustering selected by variance mapping of normalized...

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Detalles Bibliográficos
Autores principales: Acheson, Kyle, Kirrander, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536988/
https://www.ncbi.nlm.nih.gov/pubmed/37703098
http://dx.doi.org/10.1021/acs.jctc.3c00776