Kinematic reconstruction of atmospheric neutrino events in a large water Cherenkov detector with proton identication

PHYSICAL REVIEW D(2009)

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摘要
We report the development of a proton identification method for the Super-Kamiokande (SK) detector. This new tool is applied to the search for events with a single proton track, a high purity neutral current sample of interest for sterile neutrino searches. After selection using a neural network, we observe 38 events in the combined SK-I and SK-II data corresponding to 2285.1 days of exposure, with an estimated signal-to-background ratio of 1.6 to 1. Proton identification was also applied to a direct search for charged-current quasielastic (CCQE) events, obtaining a high precision sample of fully kinematically reconstructed atmospheric neutrinos, which has not been previously reported in water Cherenkov detectors. The CCQE fraction of this sample is 55%, and its neutrino (as opposed to antineutrino) fraction is 91.7 +/- 3%. We selected 78 mu- like and 47 e-like events in the SK-I and SK-II data set. With this data, a clear zenith angle distortion of the neutrino direction itself is reported in a sub-GeV sample of mu neutrinos where the lepton angular correlation to the incoming neutrino is weak. Our fit to nu(mu) -> nu(tau) oscillations using the neutrino L/E distribution of the CCQE sample alone yields a wide acceptance region compatible with our previous results and excludes the no-oscillation hypothesis at 3-sigma.
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关键词
elementary particles,neutral current,neural network,protons,standard model,hypothesis,sterile neutrino,neutrinos,neutrino oscillation,oscillations
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