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Jet Energy Calibration with Deep Learning as a Kubeflow Pipeline
Precise measurements of the energy of jets emerging from particle collisions at the LHC are essential for a vast majority of physics searches at the CMS experiment. In this study, we leverage well-established deep learning models for point clouds and CMS open data to improve the energy calibration o...
| Autores principales: | , , |
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| Lenguaje: | eng |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/s41781-023-00103-y http://cds.cern.ch/record/2869501 |