Speaker
Description
The Jiangmen Underground Neutrino Observatory (JUNO) is a state-of-the-art 20 kton liquid scintillator detector designed to achieve an unprecedented energy resolution of 3% @ 1 MeV. The energy resolution is of paramount importance for the measurement of neutrino mass ordering (NMO) through the study of reactor neutrinos at JUNO. A key factor contributing to the energy resolution in JUNO is the charge smearing of PMTs. This talk introduces a ML-based photon counting method for PMT waveforms and its application to the energy reconstruction of JUNO. By integrating the photon counting information into the charge-based likelihood function, this approach can partially mitigate the impact of the PMT charge smearing and improve the energy resolution by about 2% to 3% at different energies.
| Type of contribution | Talk: 15 minutes. |
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