Cargando…
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
Within the Phase-II upgrade of the LHC, the readout electronics of the ATLAS LAr Calorimeters is prepared for high luminosity operation expecting a pile-up of up to 200 simultaneous pp interactions. Moreover, the calorimeter signals of up to 25 subsequent collisions are overlapping, which increases...
Autor principal: | Gutsche, Christian |
---|---|
Lenguaje: | eng |
Publicado: |
2023
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2863771 |
Ejemplares similares
-
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
por: Aad, Georges, et al.
Publicado: (2022) -
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
por: Fortin, Etienne Marie
Publicado: (2021) -
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
por: Voigt, Johann Christoph
Publicado: (2023) -
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
por: Berthold, Anne-Sophie
Publicado: (2023) -
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
por: Voigt, Johann Christoph
Publicado: (2023)