Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal gen...

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Detalles Bibliográficos
Autores principales: Uboldi, Lorenzo, Ruth, David, Andrews, Michael, Wang, Michael H.L.S., Wenzel, Hans Joachim, Wu, Wanwei, Yang, Tingjun
Lenguaje:eng
Publicado: 2021
Materias:
hep-ex
Particle Physics - Experiment
physics.ins-det
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1016/j.nima.2022.166371
http://cds.cern.ch/record/2773634

Internet

https://dx.doi.org/10.1016/j.nima.2022.166371
http://cds.cern.ch/record/2773634

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