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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Journal of physics. Conference series 2018-09, Vol.1085 (4), p.42042
Hauptverfasser:	Acosta, Darin, Brinkerhoff, Andrew, Busch, Elena, Carnes, Andrew, Furic, Ivan, Gleyzer, Sergei, Kotov, Khristian, Low, Jia Fu, Madorsky, Alexander, Rorie, Jamal, Scurlock, Bobby, Shi, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Complex variables Decision trees Inelastic scattering Large Hadron Collider Lookup tables Machine learning Momentum Muons Physics Solenoids Variables
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!