| Summary: | This thesis presents an analysis of the oscillation of atmospheric neutrinos observed in Super-Kamiokande, a large underground water Cherenkov detector in Japan. The observed atmospheric neutrino events are reconstructed and selected using a newly developed maximum likelihood event reconstruction algorithm, and a Markov chain Monte Carlo technique is employed to present the results on neutrino oscillation parameters as marginalized Bayesian posterior probabilities. The result of analyzing the SK-IV data of 2520 days exposure shows a preference for normal mass hierarchy with the posterior probability of 85.9%, and the mode and the 68% credible interval of each oscillation parameter’s marginalized 1D posterior probability distribution for normal hierarchy are sin² θ₂₃=0.606⁺⁰·⁰⁴⁴₋₀.₁₁₈ and Δm²₃₂=2.13⁺⁰·¹⁷₋₀.₃₈ ×10-³ eV². === Science, Faculty of === Physics and Astronomy, Department of === Graduate
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