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Application of Transfer Learning to Neutrino Interaction Classification
Andrew Chappell, Leigh H. Whitehead
Training deep neural networks using simulations typically requires very large numbers of simulated events. This can be a large computational burden and a limitation in the performa…
Neutrino Characterisation using Convolutional Neural Networks in CHIPS water Cherenkov detectors
Josh Tingey, Simeon Bash, John Cesar +8
This work presents a novel approach to water Cherenkov neutrino detector event reconstruction and classification. Three forms of a Convolutional Neural Network have been trained to…
Detector and Beamline Simulation for Next-Generation High Energy Physics Experiments
Sunanda Banerjee, D. N. Brown, David N. Brown +31
The success of high energy physics programs relies heavily on accurate detector simulations and beam interaction modeling. The increasingly complex detector geometries and beam dyn…
Future Opportunities in Accelerator-based Neutrino Physics
Andrea Dell'Acqua, Antoni Aduszkiewicz, Markus Ahlers +140
This document summarizes the conclusions of the Neutrino Town Meeting held at CERN in October 2018 to review the neutrino field at large with the aim of defining a strategy for acc…
Neutrino Oscillations with MINOS and MINOS+
Leigh H. Whitehead
The MINOS experiment ran from 2003 until 2012 and collected a data sample including 10.71x10^20 protons-on-target (POT) of beam neutrinos, 3.36x10^20 POT of beam antineutrinos and…
Indication of Electron Neutrino Appearance from an Accelerator-produced Off-axis Muon Neutrino Beam
T2K Collaboration, K. Abe, N. Abgrall +408
The T2K experiment observes indications of appearance in data accumulated with protons on target. Six events pass all selection criteria at…