Cargando…
Optimising longitudinal and lateral calorimeter granularity for software compensation in hadronic showers using deep neural networks
We investigate the effect of longitudinal and transverse calorimeter segmentation on event-by-event software compensation for hadronic showers. To factorize out sampling and detector effects, events are simulated in which a single charged pion is shot at a homogenous lead glass calorimeter, split in...
| Autores principales: | , , |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2021
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1140/epjc/s10052-022-10031-7 http://cds.cern.ch/record/2752184 |