Super-kamiokande atmospheric neutrino analysis of matter-dependent neutrino oscillation models

dc.contributor.authorShiraishi, Kiyoshi Keola, 1978-en_US
dc.date.accessioned2009-10-07T00:19:36Z
dc.date.available2009-10-07T00:19:36Z
dc.date.issued2006en_US
dc.descriptionThesis (Ph. D.)--University of Washington, 2006.en_US
dc.description.abstractCurrent data finds that the atmospheric neutrino anomaly is best explained with numu - nutau neutrino oscillations. However, there is motivation for the Mass Varying Neutrino (MaVaN) model as an explanation for the presence of dark energy and the results of LSND. A possible consequence of said model is a bias in the neutrino mass from the electron density rho e of the matter a neutrino passes through. Using the data from Super-Kamiokande-I, numu - nutau oscillation models whose mass differences are proportional to (rhoe) n are applied to the Monte Carlo predictions for several different n values. A constant mixing angle in all densities is assumed. For each density dependence hypothesis, two sets of models are applied, which do not or do account for the air pathlength. In all of the specific models tested, the density dependent oscillations are disfavored at greater than a 3sigma level compared with 2-flavor oscillations with a fixed mass in all environments. In addition, a separate analysis which assumes maximal mixing finds that a best-fit 2-flavor oscillation of varying density dependence is consistent with no dependence on electron density within 1sigma.en_US
dc.format.extentxv, 142 p.en_US
dc.identifier.otherb57893536en_US
dc.identifier.other123957601en_US
dc.identifier.otherThesis 56501en_US
dc.identifier.urihttp://hdl.handle.net/1773/9771
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.rights.uriFor information on access and permissions, please see http://digital.lib.washington.edu/rw-faq/rights.htmlen_US
dc.subject.otherTheses--Physicsen_US
dc.titleSuper-kamiokande atmospheric neutrino analysis of matter-dependent neutrino oscillation modelsen_US
dc.typeThesisen_US

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