Starting track events in IceCube
Journal of Instrumentation IOP Publishing 16:09 (2021) c09015
Using convolutional neural networks to reconstruct energy of GeV scale IceCube neutrinos
Journal of Instrumentation IOP Publishing 16:09 (2021) c09019
Cosmic-Ray Studies with the Surface Instrumentation of IceCube
ArXiv 2108.07164 (2021)
A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors
Journal of Instrumentation 16:8 (2021)
Abstract:
IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment's photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors.Hybrid cosmic ray measurements using the IceAct telescopes in coincidence with the IceCube and IceTop detectors
ArXiv 2108.05572 (2021)