Boosted Decision Trees in the Level-1 Muon Endcap Trigger at CMS

The first implementation of a Machine Learning Algorithm inside a Level-1 trigger system at the LHC is presented. The Endcap Muon Track Finder (EMTF) at CMS uses Boosted Decision Trees (BDTs) to infer the momentum of muons in the forward region of the detector, based on 25 different variables. Combi...

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Detalles Bibliográficos
Autores principales: Acosta, Darin Edward, Brinkerhoff, Andrew Wilson, Busch, Elena Laura, Carnes, Andrew Mathew, Furic, Ivan-Kresimir, Gleyzer, Sergei, Kotov, Khristian, Low, Jia Fu, Madorsky, Alexander, Rorie, Jamal Tildon, Scurlock, Bobby, Shi, Wei
Lenguaje:eng
Publicado: 2017
Materias:
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/1085/4/042042
http://cds.cern.ch/record/2290188

Internet

https://dx.doi.org/10.1088/1742-6596/1085/4/042042
http://cds.cern.ch/record/2290188

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