End-to-end particle and event identification at the Large Hadron Collider with CMS Open Data

From particle identification to the discovery of the Higgs boson, deep learning algorithms have become an increasingly important tool for data analysis at the Large Hadron Collider (LHC). We present an innovative end-to-end deep learning approach for jet identification at the Compact Muon Solenoid (...

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Detalles Bibliográficos
Autores principales: Alison, John, An, Sitong, Bryant, Patrick, Burkle, Bjorn, Gleyzer, Sergei, Narain, Meenakshi, Paulini, Manfred, Poczos, Barnabas, Usai, Emanuele
Lenguaje:eng
Publicado: 2019
Materias:
physics.ins-det
Detectors and Experimental Techniques
hep-ex
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2698977

Internet

http://cds.cern.ch/record/2698977

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