Bulletin of the American Physical Society
Joint Fall 2022 Meeting of the Texas Section of the APS, Texas Section of the AAPT, and Zone 13 of the SPS
Volume 67, Number 11
Thursday–Saturday, October 13–15, 2022; Rice University, Houston, Texas
Session E01: Nuclear and Particle Physics I
10:30 AM–11:54 AM,
Friday, October 14, 2022
Rice University BRC
Room: Auditorium
Chair: Andrew Long
Abstract: E01.00007 : Applying the DUNE convolutional neural network to ICARUS liquid argon TPC data
11:42 AM–11:54 AM
Presenter:
Eduardo A Dagnino
(University of Houston)
Authors:
Eduardo A Dagnino
(University of Houston)
Antoni Aduszkiewicz
(University of Houston)
Daniel Cherdack
(University of Houston)
Computer scientists working in collaboration with High-Energy physicists developed a Convolutional Neural Network (CVN) for DUNE intending to achieve highly efficient and pure selections of electron and muon neutrino Charged-Current (CC) interactions. The network should provide considerable gains in time saved and overall identification accuracy. We believe the network code is flexible enough to be adapted to work with ICARUS datasets after minor changes. We trained a modified CVN in a variety of test scenarios with smaller data sets and shorter training periods. The next step will be full training using high-performance computing resources. I will describe the CVN inputs and network architecture, compare results between the published CVN results and our test runs, and present plans for our upcoming full training run.
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