Cargando…
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: | Garg, Rocky Bala, Tompkins, Lauren Alexandra |
---|---|
Lenguaje: | eng |
Publicado: |
2023
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2871421 |
Ejemplares similares
-
Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton--proton collisions at the LHC
por: Aaboud, Morad, et al.
Publicado: (2016) -
Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC
por: Aaboud, M., et al.
Publicado: (2017) -
A Measurement of the proton-proton inelastic scattering cross-section at $\sqrt{s}$ =7 TeV with the ATLAS detector at the LHC
por: Tompkins, Lauren Alexandra
Publicado: (2011) -
Quarkonium production in proton-proton and proton-lead collisions with ATLAS at the LHC
por: Arratia, Miguel
Publicado: (2016) -
Femtoscopy of proton-proton collisions at the LHC with the ALICE experiment
por: Graczykowski, Łukasz
Publicado: (2012)