6–13 Jul 2022
Bologna, Italy
Europe/Rome timezone

Direction reconstruction of atmospheric neutrinos in JUNO with machine learning method

8 Jul 2022, 19:05
1h 25m
Bologna, Italy

Bologna, Italy

Palazzo della Cultura e dei Congressi
Poster Neutrino Physics Poster Session

Speaker

Dr Zhen Liu (Institute of High Energy Physics)

Description

The Jiangmen Underground Neutrino Observatory (JUNO) is a next-generation large liquid-scintillator neutrino detector. Its main goal is the determination of neutrino mass ordering, one of the most crucial open questions for neutrinos. To enhance its sensitivity to the mass ordering, JUNO will combine the measurements of reactor anti-neutrinos at low energies with those of atmospheric neutrinos at high energies (GeV level). The sensitivity from the atmospheric neutrino measurement significantly depends on the angular resolution of the incident neutrino.
This poster presents the direction reconstruction of atmospheric neutrinos with the machine learning method. In this method, multiple features extracted from tens of thousands of PMT waveforms are utilized to characterize the direction properties of atmospheric neutrinos. And two independent machine learning models, including a deep convolutional neural network and a spherical graph neural network, are used to perform the reconstruction. Preliminary results based on full Monte Carlo simulation show great potential for the high-precision reconstruction of the neutrino direction.

In-person participation No

Primary authors

Prof. Duyang Hongyue (Institute of Frontier and Interdisciplinary Science, Shandong University) Prof. Teng Li (Institute of Frontier and Interdisciplinary Science, Shandong University) Mr Jiaxi Liu (Institute of High Energy Physics) Dr Zhen Liu (Institute of High Energy Physics)

Presentation materials