824 citations · 1.6k across the 18 of their papers we have counts for
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Reconstruction of atmospheric neutrinos in DUNE's horizontal-drift far-detector module
DUNE Collaboration, S. Abbaslu, F. Abd Alrahman +1343
This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment's (DUNE) far detector…
First Measurement of the Total Inelastic Cross-Section of Positively-Charged Kaons on Argon at Energies Between 5.0 and 7.5 GeV
DUNE Collaboration, A. Abed Abud, B. Abi +1360
ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a meas…
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…
Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector
DUNE Collaboration, A. Abed Abud, B. Abi +1253
Measurements of electrons from interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyo…
Experiment Simulation Configurations Approximating DUNE TDR
DUNE Collaboration, B. Abi, R. Acciarri +966
The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly cap…
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…