Cargando…
Development of Machine Learning based muon trigger algorithms for the Phase2 upgrade of the CMS detector
After the high-luminosity upgrade of the LHC, the muon chambers of CMS Barrel must cope with an increase in the number of interactions per bunch crossing. Therefore, new algorithmic techniques for data acquisition and processing will be necessary in preparation for such a high pile-up environment. U...
Autores principales: | Diotalevi, Tommaso, Bonacorsi, Daniele, Battilana, Carlo, Guiducci, Luigi |
---|---|
Lenguaje: | eng |
Publicado: |
SISSA
2018
|
Materias: | |
Acceso en línea: | https://dx.doi.org/10.22323/1.321.0092 http://cds.cern.ch/record/2669221 |
Ejemplares similares
-
Deep Learning fast inference on FPGA for CMS Muon Level-1 Trigger studies
por: Diotalevi, Tommaso, et al.
Publicado: (2021) -
Upgrade of the CMS muon trigger system in the barrel region
por: Rabady, Dinyar, et al.
Publicado: (2017) -
Upgrade of the CMS muon trigger system in the barrel region
por: Battilana, Carlo, et al.
Publicado: (2016) -
CMS Muon Trigger Upgrade Phase 1
por: FURIC, Ivan Kresimir
Publicado: (2014) -
Upgrades of the CMS muon detectors: from Run 3 towards HL-LHC
por: Battilana, Carlo
Publicado: (2019)