Erlangen 2026 – scientific programme
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T: Fachverband Teilchenphysik
T 2: Neutrino Physics I
T 2.7: Talk
Monday, March 16, 2026, 17:45–18:00, AudiMax
Offline data validation framework for JUNO — •Nurbakyt Amanbek1,2 and Livia Ludhova1,2 — 1GSI Helmholtzzentrum für Schwerionenforschung GmbH, Planckstr. 1, D-64291 Darmstadt, Germany — 2Institute of Physics and EC PRISMA+, Johannes Gutenberg Universität Mainz, Mainz, Germany
The Jiangmen Underground Neutrino Observatory (JUNO) is a multipurpose liquid-scintillator detector in China that aims to determine the neutrino mass ordering by measuring reactor antineutrinos at a 52.5 km baseline. The central detector contains 20 kton of liquid scintillator and is instrumented with 17,612 large (20”) PMTs and 25,600 small (3”) PMTs, providing high light yield and excellent energy resolution. After physics data taking began on August 26, 2025, JUNO reported the most precise measurements of Δ m122 and sin2θ12 from 59.1 days of data - a level of precision that requires stable detector performance and consistently low-background, high-quality data. To monitor data quality, JUNO operates a semi-automated data-validation framework that performs prompt (online) and offline monitoring. About 10% of the data are validated promptly online to allow us to quickly react in case of major problems, while more detailed offline validation is performed once the full dataset of each run becomes available. We monitor various properties at the level of single channels, events, and the whole run. We also monitor longer-term stability of the detector to identify potential slower changes. This contribution presents the offline validation workflow and highlights its essential role in securing the data quality required for JUNO’s precision oscillation program.
Keywords: JUNO; Reactor antineutrinos; Neutrino mass ordering; Data validation framework; Detector stability