35 citations · 74 across the 4 of their papers we have counts for
4 papers
Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment
DUNE Collaboration, A. Abed Abud, B. Abi +1313
A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the MeV neutrinos produced by a Galactic core-collapse supernova if one s…
Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network
DUNE Collaboration, A. Abed Abud, B. Abi +1221
Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the techn…
A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber
MicroBooNE collaboration, P. Abratenko, M. Alrashed +184
We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the…
Long-baseline neutrino oscillation physics potential of the DUNE experiment
DUNE Collaboration, B. Abi, R. Acciarri +966
The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far…