Cosmic-Ray Composition analysis at IceCube using Graph Neural Networks [HEAP]

http://arxiv.org/abs/2211.17198


The IceCube Neutrino Observatory is a multi-component detector embedded deep within the South-Pole Ice. This proceeding will discuss an analysis from an integrated operation of IceCube and its surface array, IceTop, to estimate cosmic-ray composition. The work will describe a novel graph neural network based approach for estimating the mass of primary cosmic rays, that takes advantage of signal-footprint information and reconstructed cosmic-ray air shower parameters. In addition, the work will also introduce new composition-sensitive parameters for improving the estimation of cosmic-ray composition, with the potential of improving our understanding of the high-energy muon content in cosmic-ray air showers.

Read this paper on arXiv…

P. Koundal
Thu, 1 Dec 22
26/85

Comments: N/A