The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the p → νK+ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via p → νK+ is 36.9% ± 4.9% with a background level of 0.2 ± 0.05(syst) ± 0.2(stat) events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is 9.6 x 10^33 years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies.

JUNO sensitivity on proton decay p → νK+ searches

Baldini, Wander;Mantovani, Fabio;Montuschi, Michele;Ricci, Barbara;Serafini, Andrea;Strati, Virginia;
2023

Abstract

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the p → νK+ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via p → νK+ is 36.9% ± 4.9% with a background level of 0.2 ± 0.05(syst) ± 0.2(stat) events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is 9.6 x 10^33 years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies.
2023
Abusleme, Angel; Adam, Thomas; Ahmad, Shakeel; Ahmed, Rizwan; Aiello, Sebastiano; Akram, Muhammad; An 安, Fengpeng 丰鹏; An 安, Qi 琪; Andronico, Giuseppe;...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2524934
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