PoS - Proceedings of Science
Volume 414 - 41st International Conference on High Energy physics (ICHEP2022) - Poster Session
Reconstruction of atmospheric neutrino events at JUNO
R. Wirth*, M. Rifai, M. Molla Colomer  on behalf of the JUNO collaboration
Full text: pdf
Pre-published on: December 16, 2022
Published on: June 15, 2023
The Jiangmen Underground Neutrino Observatory (JUNO) is a 20 kt liquid scintillation detector, which will be completed in 2023 as the largest of its kind. JUNO aims to determine the neutrino mass ordering by observing the energy dependent oscillation probabilities of reactor anti-neutrinos.
JUNOs large volume provides the opportunity to detect atmospheric neutrino events with lower energies than today’s large Cherenkov experiments. As atmospheric neutrinos reach the detector from all directions, partially experiencing the matter effect, they are especially interesting for observing the neutrino mass ordering via the matter effects on their oscillation probabilities. This article presents the preliminary performance of direction and energy reconstruction methods for atmospheric neutrino events at JUNO. The former uses a traditional approach, based on the reconstruction of the photon emission topology in the JUNO detector. For the energy reconstruction, a traditional approach as well as a machine learning based using Graph Convolutional Networks, are shown.
DOI: https://doi.org/10.22323/1.414.1114
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.