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Machine learning for real-time processing of ATLAS liquid argon calorimeter signals with FPGAs
The ATLAS experiment at CERN measures energy of proton-proton (p-p) collisions with a repetition frequency of 40 MHz at the Large Hadron Collider (LHC). The readout electronics of liquid-argon (LAr) calorimeters are being prepared for high luminosity-LHC (HL-LHC) operation as part of the phase-II up...
Autor principal: | Chiedde, Nemer |
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Lenguaje: | eng |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1748-0221/17/04/C04010 http://cds.cern.ch/record/2806560 |
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