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A measurement of the energy dependence of antineutrino disappearance at the Daya Bay Reactor Neutrino Experiment is reported. Electron antineutrinos ($overline{ u}_{e}$) from six $2.9$ GW$_{rm th}$ reactors were detected with six detectors deployed i n two near (effective baselines 512 m and 561 m) and one far (1579 m) underground experimental halls. Using 217 days of data, 41589 (203809 and 92912) antineutrino candidates were detected in the far hall (near halls). An improved measurement of the oscillation amplitude $sin^{2}2theta_{13} = 0.090^{+0.008}_{-0.009} $ and the first direct measurement of the $overline{ u}_{e}$ mass-squared difference $|Delta m^{2}_{ee}|= (2.59_{-0.20}^{+0.19}) times 10^{-3} {rm eV}^2 $ is obtained using the observed $overline{ u}_{e}$ rates and energy spectra in a three-neutrino framework. This value of $|Delta m^{2}_{ee}|$ is consistent with $|Delta m^{2}_{mumu}|$ measured by muon neutrino disappearance, supporting the three-flavor oscillation model.
Experiment E949 at Brookhaven National Laboratory has observed three new events consistent with the decay K+ => pi+,nu,nubar in the pion momentum region 140 < P_pi < 199 MeV/c in an exposure of 1.71e12 stopped kaons with an estimated total background of 0.93+-0.17(stat.)+0.32-0.24(syst.) events. This brings the total number of observed K+ => pi+,nu,nubar events to seven. Combining this observation with previous results, assuming the pion spectrum predicted by the standard model, results in a branching ratio of (1.73+1.15-1.05)e-10. An interpretation of the results for alternative models of the decay K^ => pi+,nothing is also presented.
179 - E949 Collaboration 2008
Three events for the decay K+ => pi+,nu,nubar have been observed in the pion momentum region below the K+ => pi+,pi0 peak, 140 < P_pi < 199 MeV/c, with an estimated background of 0.93+-0.17(stat.)+0.32-0.24(syst.) events. Combining this observation w ith previously reported results yields a branching ratio of B(K+ => pi+,nu,nubar) = (1.73+1.15-1.05)e-10 consistent with the standard model prediction.
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