A New Method for Finding Point Sources in High-energy Neutrino Data
Ke Fang, M. Coleman Miller

TL;DR
This paper introduces a novel maximum likelihood method utilizing pairwise angular separations to identify point sources of high-energy neutrinos more efficiently and accurately than existing techniques.
Contribution
The proposed method improves source detection sensitivity by incorporating angular resolution and pairwise data, reducing errors and computational costs compared to current approaches.
Findings
Reduces false positives and negatives with better angular resolution.
More computationally efficient for large datasets.
Effective for angular resolutions of a few degrees or better.
Abstract
The IceCube collaboration has reported the first detection of high-energy astrophysical neutrinos including high-energy starting events, but no individual sources have been identified. It is therefore important to develop the most sensitive and efficient possible algorithms to identify point sources of these neutrinos. The most popular current method works by exploring a dense grid of possible directions to individual sources, and identifying the single direction with the maximum probability of having produced multiple detected neutrinos. This method has numerous strengths, but it is computationally intensive and, because it focuses on the single best location for a point source, additional point sources are not included in the evidence. We propose a new maximum likelihood method that uses the angular separations between all pairs of neutrinos in the data. Unlike existing…
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