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Novel jet observables from machine learning

Abstract Previous studies have demonstrated the utility and applicability of machine learning techniques to jet physics. In this paper, we construct new observables for the discrimination of jets from different originating particles exclusively from information identified by the machine. The approac...

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Detalles Bibliográficos
Principais autores: Kaustuv Datta, Andrew J. Larkoski
Formato: Artigo
Idioma:Inglês
Publicado: SpringerOpen 2018-03-01
Series:Journal of High Energy Physics
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Acceso en liña:http://link.springer.com/article/10.1007/JHEP03(2018)086
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