End-to-End Jet Classification of Boosted Top Quarks with CMS Open Data

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We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector...

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Detalles Bibliográficos
Autores principales: Andrews, Michael, Burkle, Bjorn, Chen, Yi-fan, DiCroce, Davide, Gleyzer, Sergei, Heintz, Ulrich, Narain, Meenakshi, Paulini, Manfred, Pervan, Nikolas, Shafi, Yusef, Sun, Wei, Usai, Emanuele, Yang, Kun
Lenguaje:eng
Publicado: 2021
Materias:
hep-ex
Particle Physics - Experiment
cs.LG
Computing and Computers
cs.CV
physics.data-an
Other Fields of Physics
Acceso en línea:https://dx.doi.org/10.1051/epjconf/202125104030
https://dx.doi.org/10.1103/PhysRevD.105.052008
http://cds.cern.ch/record/2780774

Internet

https://dx.doi.org/10.1051/epjconf/202125104030
https://dx.doi.org/10.1103/PhysRevD.105.052008
http://cds.cern.ch/record/2780774

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