Ponente
Descripción
The IceCube Neutrino Observatory, located under 1.4 km of Antarctic ice,
instruments a cubic kilometer of ice with 5,160 optical modules that detect
Cherenkov radiation originating from neutrino interactions. The more
densely instrumented center, DeepCore, aims to detect atmospheric neutrinos
at 10-GeV scales to improve important measurements of fundamental neutrino
properties such as the oscillation parameters and to search for
non-standard interactions. Sensitivity to oscillation parameters, dependent
on the distance traveled over the neutrino energy (L/E), is limited in
IceCube by the resolution of the arrival angle (which determines L) and
energy (E). Event reconstruction improvements can therefore directly lead
to advancements in oscillation results. This work uses a Convolutional
Neural Network (CNN) to reconstruct the energy of 10-GeV scale neutrino
events in IceCube, providing results with competitive resolutions and
faster runtimes than previous likelihood-based methods.
| Affiliation | MSU |
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