Neutrino Astrophysics with the Antares Telescope

ISBN-13: 9783319387154 / Angielski / Miękka / 2016 / 119 str.

Vladimir Kulikovskiy

Opis

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. 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).

Spis treści

Introduction.- The ANTARES Detector.- Simulation of the ANTARES Detector Work.- Event Reconstruction and Data Selection.- Fermi Bubbles Analysis.- Conclusions.

O autorze

2006 – 2008 Master thesis, Moscow State University. KM3NeT detector simulations.
2009 – 2011 INFN fellow, Genoa. Supernova detection with ANTARES.
2011 –  2013 PhD thesis, Genoa & Paris VII. Fermi bubbles analysis with the ANTARES data. Neutrino mass hierarchy study with ORCA.
2014 – 2015 INFN Postdoc, Laboratori Nazionali del Sud. KM3NeT detector construction & tests. KM3NeT sensitivity to Dark Matter.

Blurb

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).