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Multi-Messenger Analysis of KM3NeT and CTA data to distinguish between leptonic and hadronic emission scenarios

Authors: Tim Unbehaun;

Multi-Messenger Analysis of KM3NeT and CTA data to distinguish between leptonic and hadronic emission scenarios

Abstract

Neutral particles like photons and neutrinos are suited for the study of galactic sources of very-high-energy γ-rays. While the source morphologies and spectra of galactic sources have been studied based on electromagnetic observations, it is challenging to distinguish leptonic versus hadronic production of γ-rays based on electromagnetic observations alone. Since cosmic neutrinos are expected only from hadronic interactions, observations of cosmic neutrinos in correlation with γ-ray emission can shed some light on the nature of γ-ray production mechanisms. The combined analysis of data from γ-ray and neutrino observatories will yield a more comprehensive picture of these sources. The Cherenkov Telescope Array (CTA) is the next generation ground-based observatory for γ-ray astronomy at very-high energies, which will significantly improve the sensitivity of high-energy γ-ray observations. The KM3NeT collaboration has started to build a multi-kilometer volume neutrino telescope in the Mediterranean sea, the ARCA detector, which will complement neutrino telescopes located in the Northern hemisphere and substantially improve the sensitivity to galactic cosmic neutrinos. In this contribution, the results of a combined likelihood analysis of simulated data events from KM3NeT/ARCA and CTA are presented, showing how a combined analysis can constrain the contribution of hadronic and leptonic emission processes to the observed γ-ray emission.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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