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T: Fachverband Teilchenphysik

T 10: Neutrino Astronomy I

T 10.3: Talk

Monday, March 31, 2025, 17:15–17:30, VG 1.105

Stacking Likelihood Analysis of Extreme Blazars with IceCube Public Data — •Juan Manuel Cano Vila^1,2, Chiara Bellenghi¹, and Paolo Padovani³ — ¹Technical University of Munich, TUM School of Natural Sciences, Department of Physics, James-Franck-Straße 1, D-85748 Garching bei München, Germany — ²Arnold Sommerfeld Center, Ludwig-Maximilians University, 80333 Munich, Germany — ³European Southern Observatory, Karl- Schwarzschild-Straße 2, D-85748 Garching bei München, Germany

Since the confirmation of the existence of high-energy astrophysical neutrinos more than 10 years ago, researchers have been trying to identify which kind of objects emit them. The results have been limited, and the origin of the majority of this astrophysical neutrino flux remains unknown. For the last few years, IceCube has released several datasets to the public that allow any research group to test their hypothesis. One of the available tools designed to study this data is SkyLLH, an open source Python package that provides a framework for implementing custom likelihood functions and executing log-likelihood ratio hypothesis tests. In this project, we developed a new functionality to perform stacking log-likelihood analysis, where one studies the joint signal from multiple selected sources, which enhances the statistics by a population-wide study and allows to test different hypothesis by selecting the weights of each source of the population. We apply this tool to a selected population of blazars characterized by their extreme luminosities in radio and γ-rays.

Keywords: Neutrino Astronomy; Blazars; Likelihood Analysis; Open Software