Neutrino Fingerprints: Image-Based Encodings of IceCube Events for CNN Direction Reconstruction
Reconstructing the direction of incoming neutrinos in the IceCube Neutrino Observatory is an important problem in astrophysics. The public IceCube--Neutrinos in Deep Ice Kaggle competition provided 140 million simulated events to benchmark reconstruction techniques. To address this challenge from a novel perspective we introduce neutrino fingerprints compact $72 \times 72 \times 3$ images in which each pixel represents a single detector, with pulse timing and charge statistics encoded as color channels. This representation transforms sparse, irregular pulse data into dense images suitable for convolutional processing. Our ResNet18 model achieves a mean angular error of $1.10$ rad, indicat...
| Authors | Floriano Tori, Brecht Verbeken, Vincent Ginis |
|---|---|
| Primary category | astro-ph.IM |
| Published | 1 June 2026 |
| Last updated at source | 1 June 2026 |
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