Cargando…
Identification of Jets Containing $b$-Hadrons with Recurrent Neural Networks at the ATLAS Experiment
A novel $b$-jet identification algorithm is constructed with a Recurrent Neural Network (RNN) at the ATLAS experiment at the CERN Large Hadron Collider. The RNN based $b$-tagging algorithm processes charged particle tracks associated to jets without reliance on secondary vertex finding, and can augm...
Autor principal: | The ATLAS collaboration |
---|---|
Lenguaje: | eng |
Publicado: |
2017
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2255226 |
Ejemplares similares
-
Identification of Jets Containing b-Hadrons with Recurrent Neural Networks at the ATLAS Experiment
por: Jiang, Zihao
Publicado: (2017) -
Topological $b$-hadron decay reconstruction and identification of $b$-jets with the JetFitter package in the ATLAS experiment at the LHC
por: The ATLAS collaboration
Publicado: (2018) -
Identification of hadronic tau lepton decays using neural networks in the ATLAS experiment
por: The ATLAS collaboration
Publicado: (2019) -
Identification of Jets Containing b-Hadrons with Recurrent Neural Networks at the ATLAS Experiment
por: Guest, Daniel Hay
Publicado: (2017) -
Graph Neural Network Jet Flavour Tagging with the ATLAS Detector
por: The ATLAS collaboration
Publicado: (2022)