Performance of a machine learning algorithm for predicting muon multiplicity
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- uploaded July 5, 2021
Discussion timeslot (ZOOM-Meeting): 15. July 2021 - 18:00
ZOOM-Meeting URL: https://desy.zoom.us/j/91999581729
ZOOM-Meeting ID: 91999581729
ZOOM-Meeting Passcode: ICRC2021
Corresponding Session: https://icrc2021-venue.desy.de/channel/37-Reconstruction-amp-Analysis-Techniques-NU/126
Live-Stream URL: https://icrc2021-venue.desy.de/livestream/Discussion-05/6
Abstract:
'We present here the performance of a machine learning-based algorithm to predict the muon multiplicity using a simulated dataset in which the trigger condition was varied. We also show the performance of this algorithm is selecting interesting events in the prototype detector at TIFR.'
Authors: Lakshmi Murgod
Co-Authors: Deepak Samuel | SOURAV DUTTA
Indico-ID: 170
Proceeding URL: https://pos.sissa.it/395/1024
Categories:
Neutrino, Scientific Contributions
Presenter:
Lakshmi Murgod
