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Machine Learning for Absorption Cross Sections

[Image: see text] We present a machine learning (ML) method to accelerate the nuclear ensemble approach (NEA) for computing absorption cross sections. ML-NEA is used to calculate cross sections on vast ensembles of nuclear geometries to reduce the error due to insufficient statistical sampling. The...

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Detalles Bibliográficos
Autores principales: Xue, Bao-Xin, Barbatti, Mario, Dral, Pavlo O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511037/
https://www.ncbi.nlm.nih.gov/pubmed/32786977
http://dx.doi.org/10.1021/acs.jpca.0c05310

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