“Search for features in astrophysical objects close to cosmic neutrinos”. An indirect approach to cosmic neutrino association with astrophysical objects

Project Summary

The work proposed here is in the field of Astroparticle Physics, a sub-branch of Physics dealing with the understanding of the Universe through the detection of gamma rays, neutrinos, gravitational waves and cosmic rays. In particular, here, we focus on a search for a connection between high-energy neutrinos and gamma rays in the extragalactic sky. Two large observatories have been designed to be able to detect high-energy neutrinos from astrophysical environments: IceCube and KM3NeT. IceCube already has collected 10-years of data, which resulted in a catalogue of neutrinos having a high probability of being of cosmic origin, while KM3NeT is an observatory under construction. The significance of the signal of IceCube cosmic neutrinos shows that still no firm conclusion can be drawn on the association of these with astrophysical objects. This Master project concerns an indirect search for neutrino associations with astrophysical objects using a statistical inference approach, taking advantage of the published neutrino lists, catalogues of astrophysical objects, and open data from the Fermi observatory. Technically, the project needs the development of a full Python analysis chain using Deep Learning.

Yvonne Becherini