Conditional normalizing flows for IceCube event reconstruction
Thorsten Gl\"usenkamp (for the IceCube collaboration)

TL;DR
This paper introduces the use of conditional normalizing flows for reconstructing the direction and energy of neutrino events in IceCube, effectively modeling complex uncertainties and ice properties to improve event analysis.
Contribution
It presents a novel application of conditional normalizing flows to IceCube event reconstruction, capturing systematic uncertainties and ice optical properties for better inference.
Findings
Normalizing flows correctly incorporate ice optical properties.
Differential entropy correlates with photon absorption and track length.
Coverage maintained even with low photon counts.
Abstract
The IceCube Neutrino Observatory is a cubic-kilometer high-energy neutrino detector deployed in the Antarctic ice. Two major event classes are charged-current electron and muon neutrino interactions. In this contribution, we discuss the inference of direction and energy for these classes using conditional normalizing flows. They allow to derive a posterior distribution for each individual event based on the raw data that can include systematic uncertainties, which makes them very promising for next-generation reconstructions. For each normalizing flow we use the differential entropy and the KL-divergence to its maximum entropy approximation to interpret the results. The normalizing flows correctly incorporate complex optical properties of the Antarctic ice and their relation to the embedded detector. For showers, the differential entropy increases in regions of high photon absorption…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Neutrino Physics Research
MethodsNormalizing Flows
