Abstract
To constrain the contribution of source populations to the observed neutrino sky, we consider isotropic and anisotropic components of the diffuse neutrino data. We simulate through-going muon neutrino events by applying statistical distributions for the fluxes of extragalactic sources and investigate the sensitivities of current (IceCube) and future (IceCube-Gen2 and KM3NeT) experiments. The angular power spectrum is a powerful probe to assess the angular characteristics of neutrino data and we can already constrain rare and bright sources with current IceCube data. In addition, decaying and annihilating very heavy dark matter is a potential neutrino source, as suggested by the observed excess in the High-Energy Starting Event dataset. We apply an angular power spectrum analysis to HESE data for different dark matter models, allowing us to interpret the observed neutrino sky and perform a sensitivity forecast.
Highlights
Level [17, 18]
The anisotropy of the neutrino events can be assessed through the angular power spectrum (APS), which represents the fluctuations as a function of the angular scale
We look for constraints at 95% confidence level (CL), which is equivalent to p = 0.05
Summary
Level [17, 18]. Even though these could still be caused by atmospheric neutrino background, if confirmed, the blazars will be established as one of the contributing sources of high-energy neutrinos through cosmic ray acceleration followed by hadronic interactions. A galactic contribution is predicted, which is found to be relatively small and we will not consider this in our analysis [26, 27] Another method in order to reveal sources that give dominant contribution to the measured diffuse flux, is by studying angular clustering of registered events [28,29,30] and is shown to be more efficient than the conventional point-source searches [20] for individually bright, rare source populations such as blazars [30]. [30] by adopting more realistic simulations of the expected sky map of neutrino events of given exposure By repeating these Monte Carlo simulations, we make error estimates more robust by taking cross correlations between different multipole bins fully into account.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
