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Advances in developing deep neural networks for finding primary vertices in proton-proton collisions at the LHC
We have been studying the use of deep neural networks (DNNs) to identify and locate primary vertices (PVs) in proton-proton collisions at the LHC. Earlier work focused on finding primary vertices in simulated LHCb data using a hybrid approach that started with kernel density estimators (KDEs) derive...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
2023
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2871421 |