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Neutrino Astrophysics with the ANTARES Telescope

This thesis is devoted to ANTARES, the first underwater neutrino telescope in the Mediterranean sea. As the main scientific analysis, a search for high-energy neutrino emission from the region of the Fermi bubbles has been performed using data from the ANTARES detector. A method for the background e...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kulikovskiy, Vladimir (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Springer Theses, Recognizing Outstanding Ph.D. Research,
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Neutrino Astrophysics with the ANTARES Telescope  |h [electronic resource] /  |c by Vladimir Kulikovskiy. 
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300 |a XIII, 119 p. 85 illus., 34 illus. in color.  |b online resource. 
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505 0 |a Introduction -- The ANTARES Detector -- Simulation of the ANTARES Detector Work -- Event Reconstruction and Data Selection -- Fermi Bubbles Analysis -- Conclusions. 
520 |a This thesis is devoted to ANTARES, the first underwater neutrino telescope in the Mediterranean sea. As the main scientific analysis, a search for high-energy neutrino emission from the region of the Fermi bubbles has been performed using data from the ANTARES detector. A method for the background estimation using off-zones has been developed specially for this measurement. A new likelihood for the limits calculation which treats both observations in the on-zone and in the off-zone in the similar way and also includes different systematic uncertainties has been constructed. The analysis of 2008-2011 ANTARES data yielded a 1.2 σ  excess of events in the Fermi bubble regions, compatible with the no-signal hypothesis. For the optimistic case of no energy cutoff in the flux, the upper limit is within a factor of three of the prediction of the purely hadronic model based on the measured gamma-ray flux. The sensitivity improves as more data are accumulated (more than 65% gain in the sensitivity is expected once 2012-2016 data are added to the analysis). 
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