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Segmentation of EM showers for neutrino experiments with deep graph neural networks
We introduce a first-ever algorithm for the reconstruction of multiple showers from the data collected with electromagnetic (EM) sampling calorimeters. Such detectors are widely used in High Energy Physics to measure the energy and kinematics of in-going particles. In this work, we consider the...
| Autores principales: | , , |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1088/1748-0221/16/12/P12035 http://cds.cern.ch/record/2804131 |