The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the ...Hyper-Kamiokande experiment. It is found that applying these techniques leads to an improvement of more than 50% in the energy resolution for all lepton energies compared to an approach based upon lookup tables. Machine learning techniques can be easily applied to different detector configurations and the results are comparable to likelihood-function based techniques that are currently used.
Using the CLEO II detector operating at the
e
+
e
− Cornell Electron Storage Ring (CESR), we present evidence for new decay modes of the
Ξ
c
+ into
Ξ
0
π
+,
Ξ
0
π
+
π
0, and
Ξ
0
π
+
π
−
π
+. The ...branching ratios of these decay modes, relative to
Ξ
c
+→
Ξ
−
π
+
π
+, have been measured to be 0.55±0.13±0.09, 2.34±0.57±0.37, and 1.74±0.42±0.27, respectively.
The TITUS, Tokai Intermediate Tank for Unoscillated Spectrum, detector, is a proposed Gd-doped Water Cherenkov tank with a magnetised muon range detector downstream. It is located at J-PARC at about ...2 km from the neutrino target and it is proposed as a potential near detector for the Hyper-Kamiokande experiment. Assuming a beam power of 1.3 MW and 27.05 x 10^{21} protons-on-target the sensitivity to CP and mixing parameters achieved by Hyper-Kamiokande with TITUS as a near detector is presented. Also, the potential of the detector for cross sections and Standard Model parameter determination, supernova neutrino and dark matter are shown.
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