SNO+

Abstract:

SNO+ is a large liquid scintillator-based experiment located 2km underground at SNOLAB, Sudbury, Canada. It reuses the Sudbury Neutrino Observatory detector, consisting of a 12m diameter acrylic vessel which will be filled with about 780 tonnes of ultra-pure liquid scintillator. Designed as a multipurpose neutrino experiment, the primary goal of SNO+ is a search for the neutrinoless double-beta decay (0$\nu\beta\beta$) of 130Te. In Phase I, the detector will be loaded with 0.3% natural tellurium, corresponding to nearly 800 kg of 130Te, with an expected effective Majorana neutrino mass sensitivity in the region of 55-133 meV, just above the inverted mass hierarchy. Recently, the possibility of deploying up to ten times more natural tellurium has been investigated, which would enable SNO+ to achieve sensitivity deep into the parameter space for the inverted neutrino mass hierarchy in the future. Additionally, SNO+ aims to measure reactor antineutrino oscillations, low-energy solar neutrinos, and geoneutrinos, to be sensitive to supernova neutrinos, and to search for exotic physics. A first phase with the detector filled with water will begin soon, with the scintillator phase expected to start after a few months of water data taking. The 0$\nu\beta\beta$ Phase I is foreseen for 2017.

Abstract:

The $\mathrm{SNO}+$ Collaboration reports the first evidence of ${}^8\mathrm{B}$ solar neutrinos interacting on ${}^{13}\mathrm{C}$ nuclei. The charged current interaction proceeds through ${}^{13}\mathrm{C}+{\nu }_e{\to }^{13}\mathrm{N}+e^{-}$ which is followed, with a 10 minute half life, by ${}^{13}\mathrm{N}{\to }^{13}\mathrm{C}+e^{+}+{\nu }_e$ . The detection strategy is based on the delayed coincidence between the electron and the positron. Evidence for the charged current signal is presented with a significance of $4.2\sigma$ . Using the natural abundance of ${}^{13}\mathrm{C}$ present in the scintillator, 5.7 metric tons of ${}^{13}\mathrm{C}$ over 231 days of data were used in this analysis. The ${5.6}_{-2.3}^{+3.0}$ observed events in the data set are consistent with the expectation of ${4.7}_{-1.3}^{+0.6}$ events. This result is the second real-time measurement of CC interactions of ${}^8\mathrm{B}$ neutrinos with nuclei and constitutes the lowest energy observation of neutrino interactions on ${}^{13}\mathrm{C}$ generally. This enables the first direct measurement of the CC ${\nu }_e$ reaction to the ground state of ${}^{13}\mathrm{N}$ , yielding an average cross section of $({16.1}_{-6.7}^{+8.5}(\mathrm{stat}\mathrm{.}{)}_{-2.7}^{+1.6}(\mathrm{syst}\mathrm{.}))\times {10}^{-43}{\mathrm{cm}}^2$ over the relevant ${}^8\mathrm{B}$ solar neutrino energies.

Abstract:

$\mathrm{SNO}+$ Collaboration reports its second spectral analysis of reactor antineutrino oscillation using 286 ton-yr of new data. The measured energies of reactor antineutrino candidates were fitted to obtain the second-most precise determination of the neutrino mass-squared difference $\mathrm{\Delta }{m}_{21}^2=({7.96}_{-0.42}^{+0.48})\times {10}^{-5}{\mathrm{eV}}^2$ . Constraining $\mathrm{\Delta }{m}_{21}^2$ and ${\sin }^2{\theta }_{12}$ with measurements from long-baseline reactor antineutrino and solar neutrino experiments yields $\mathrm{\Delta }{m}_{21}^2=({7.58}_{-0.17}^{+0.18})\times {10}^{-5}{\mathrm{eV}}^2$ and ${\sin }^2{\theta }_{12}=0.308\pm 0.013$ . This fit also yields a first measurement of the flux of geoneutrinos in the Western Hemisphere, with ${73}_{-43}^{+47}$ TNU at $\mathrm{SNO}+$ .

Abstract:

In the DEAP-3600 dark matter search experiment, precise reconstruction of the positions of scattering events in liquid argon is key for background rejection and defining a fiducial volume that enhances dark matter candidate events identification. This paper describes three distinct position reconstruction algorithms employed by DEAP-3600, leveraging the spatial and temporal information provided by photomultipliers surrounding a spherical liquid argon vessel. Two of these methods are maximum-likelihood algorithms: the first uses the spatial distribution of detected photoelectrons, while the second incorporates timing information from the detected scintillation light. Additionally, a machine learning approach based on the pattern of photoelectron counts across the photomultipliers is explored.