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A deep neural network method for analyzing the CMS High Granularity Calorimeter (HGCAL) events
For the High Luminosity LHC, the CMS collaboration made the ambitious choice of a high granularity design to replace the existing endcap calorimeters. Thousands of particles coming from the multiple interactions create showers in the calorimeters, depositing energy simultaneously in adjacent cells....
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1051/epjconf/202024502003 http://cds.cern.ch/record/2756299 |