Abstract

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment's photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors.

Highlights

  • - LOCALIZATION AND BROADBAND FOLLOW-UP OF THE GRAVITATIONALWAVE TRANSIENT GW150914 B

  • : IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole

  • These include using effective photon arrival probability distribution function (PDF) from averaged stochastic tracks instead of minimally ionizing tracks, including non-uniform photo-multiplier noise modeling, removing photons that might arise from large stochastic losses, and convolving the firstorder statistic PDF with an energy-dependent Gaussian kernel, all of which are described in more detail in [26]

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Summary

Previous algorithms

This section illustrates a typical reconstruction process and in this context describes various existing reconstructions that are useful to understand the benefits of the new approach. Some of the details have been already partially covered in refs. [16] and [17]

Angular reconstruction
Uncertainty estimation
New algorithm
Performance comparisons
Angular resolution
Runtime
Discussion and outlook
A Parametrizations of track orientations
Tangent plane parametrization
Findings
B Technical details of the uncertainty estimation
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