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Application of Machine Learning for Energy Reconstruction in the ATLAS Liquid Argon Calorimeter
The beam intensity of the Large Hadron Collider will be significantly increased during the Phase-II long shut down of 2024-2026. Signal processing techniques that are used to extract the energy of detected particles in ATLAS will suffer a significant loss in performance under these conditions. This...
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| Lenguaje: | eng |
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2021
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| Acceso en línea: | http://cds.cern.ch/record/2778208 |