JUNO is a multi-purpose neutrino observatory under construction in the south of China. This publication presents new sensitivity estimates for the measurement of the Δm231, Δm221, sin2θ12, and sin2θ13 oscillation parameters using reactor antineutrinos, which is one of the primary physics goals of the experiment. The sensitivities are obtained using the best knowledge available to date on the location and overburden of the experimental site, the nuclear reactors in the surrounding area and beyond, the detector response uncertainties, and the reactor antineutrino spectral shape constraints expected from the TAO satellite detector. It is found that the Δm221 and sin2θ12 oscillation parameters will be determined to better than 0.5% precision in six years of data collection. In the same period, the Δm231 parameter will be determined to about 0.2% precision for each mass ordering hypothesis. The new precision represents approximately an order of magnitude improvement over existing constraints

Sub-percent Precision Measurement of Neutrino Oscillation Parameters with JUNO

Andrea Serafini;Andrea Triossi62;
2022

Abstract

JUNO is a multi-purpose neutrino observatory under construction in the south of China. This publication presents new sensitivity estimates for the measurement of the Δm231, Δm221, sin2θ12, and sin2θ13 oscillation parameters using reactor antineutrinos, which is one of the primary physics goals of the experiment. The sensitivities are obtained using the best knowledge available to date on the location and overburden of the experimental site, the nuclear reactors in the surrounding area and beyond, the detector response uncertainties, and the reactor antineutrino spectral shape constraints expected from the TAO satellite detector. It is found that the Δm221 and sin2θ12 oscillation parameters will be determined to better than 0.5% precision in six years of data collection. In the same period, the Δm231 parameter will be determined to about 0.2% precision for each mass ordering hypothesis. The new precision represents approximately an order of magnitude improvement over existing constraints
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3466518
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