Neutrino Flavor Sensitivity of Large Liquid Scintillator Detectors
Loo, K., Bick, D., Enqvist, T., Hellgartner, D., Kaiser, M., Lorenz, S., Meloni, M., Meyer, M., Möllenberg, R., Oberauer, L., Soiron, M., Smirnov, M., Trzaska, W., Wonsak, B., & Wurm, M. (2015). Neutrino Flavor Sensitivity of Large Liquid Scintillator Detectors. In 13th International Conference on Topics in Astroparticle and Underground Physics, TAUP 2013 (pp. 488-494). Elsevier BV. Physics Procedia, 61. https://doi.org/10.1016/j.phpro.2014.12.112
Published inPhysics Procedia
Loo, Kai |
Bick, D. |
© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Scintillator detectors are known for their good light yield, energy resolution, timing characteristics and pulse shape discrimination capabilities. These features make the next-generation liquid scintillation detector LENA (Low Energy Neutrino Astronomy) the optimal choice for a wide range of astro-particle topics including supernova-, solar-, and geo neutrinos. In addition to the excellent calorimetric and timing properties, scintillartor detectors (LSDs) are also capable of topology reconstruction sufficient to discriminate with adequate efficiency between electron and muon neutrino induced charge current events and neutral current events in the GeV energy range. This feature makes LENA a competitive tool for the determination of the mass hierarchy (MH) with long baseline neutrino beams such as the proposed CN2PY beam (2288 km). This work summarizes the status of the current work on track reconstruction schemes and discusses the sensitivity limit for the neutrino mass hierarchy measurement with LENA. ...
ConferenceInternational Conference on Topics in Astroparticle and Underground Physics
Is part of publication13th International Conference on Topics in Astroparticle and Underground Physics, TAUP 2013
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Except where otherwise noted, this item's license is described as © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Loo, Kai (University of Jyväskylä, 2016)
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