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Graph Neural Networks for Low-Energy Event Classification & Reconstruction in IceCube. (arXiv:2209.03042v2 [hep-ex] UPDATED)
Oct. 11, 2022, 1:14 a.m. | R. Abbasi, M. Ackermann, J. Adams, N. Aggarwal, J. A. Aguilar, M. Ahlers, M. Ahrens, J.M. Alameddine, A. A. Alves Jr., N. M. Amin, K. Andeen, T. Ander
cs.LG updates on arXiv.org arxiv.org
IceCube, a cubic-kilometer array of optical sensors built to detect
atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed
1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The
classification and reconstruction of events from the in-ice detectors play a
central role in the analysis of data from IceCube. Reconstructing and
classifying events is a challenge due to the irregular detector geometry,
inhomogeneous scattering and absorption of light in the …
arxiv classification energy event graph graph neural networks low low-energy networks neural networks
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