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Development and commissioning of a machine learning algorithm for real time reconstruction of electromagnetic showers with a scintillating fibres tracker
This thesis approaches the problem of reconstructing electromagnetic showers in real time using a tracking detector interleaved with other layers serving as absorbing material. It finds immediate application in experiments such as SHiP and SND@LHC, which use calorimeters made of emulsion bricks inte...
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| Lenguaje: | eng |
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2022
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| Acceso en línea: | http://cds.cern.ch/record/2803846 |