Interpretable machine learning approach for electron antineutrino
selection in a large liquid scintillator detector
Interpretable machine learning approach for electron antineutrino
selection in a large liquid scintillator detector
Several neutrino detectors, KamLAND, Daya Bay, Double Chooz, RENO, and the forthcoming large-scale JUNO, rely on liquid scintillator to detect reactor antineutrino interactions. In this context, inverse beta decay represents the golden channel for antineutrino detection, providing a pair of correlated events, thus a strong experimental signature to distinguish the …