A Possible Two-component Flux for the High Energy Neutrino Events at IceCube

TL;DR

This paper proposes a two-component flux model to better explain IceCube's high-energy neutrino data, addressing spectral gaps and flavor composition, and highlights the importance of testing this hypothesis with future data.

Contribution

It introduces a two-component astrophysical neutrino flux model that improves data fit over single-component models and emphasizes the significance of flavor composition analysis.

Findings

Two-component flux explains the energy gap between 400 TeV and 1 PeV.

The model better fits the observed track to shower ratio.

It highlights the importance of flavor composition in interpreting neutrino sources.

Abstract

Understanding the spectral and flavor composition of the astrophysical neutrino flux responsible for the recently observed ultra-high energy events at IceCube is of great importance for both astrophysics and particle physics. We perform a statistical likelihood analysis to the 3-year IceCube data and derive the allowed range of the spectral index and flux normalization for various well-motivated physical flavor compositions at source. While most of the existing analyses so far assume the flavor composition of the neutrinos at an astrophysical source to be (1:2:0), it seems rather unnatural to assume only one type of source, once we recognize the possibility of at least two physical sources. Bearing this in mind, we entertain the possibility of a two-component source for the analysis of IceCube data. It appears that our two component hypothesis explains some key features of the data better than a single-component scenario, i.e it addresses the apparent energy gap between 400 TeV to about 1 PeV and easily accommodates the observed track to shower ratio. Given the extreme importance of the flavor composition for the correct interpretation of the underlying astrophysical processes as well as for the ramification for particle physics, this two-component flux should be tested as more data is accumulated.