Improvement in Fast Particle Track Reconstruction with Robust Statistics
M. G. Aartsen, R. Abbasi, Y. Abdou, M. Ackermann, J. Adams, J. A., Aguilar, M. Ahlers, D. Altmann, J. Auffenberg, X. Bai, M. Baker, S. W., Barwick, V. Baum, R. Bay, J. J. Beatty, S. Bechet, J. Becker Tjus, K.-H., Becker, M. L. Benabderrahmane, S. BenZvi, P. Berghaus, D. Berley

TL;DR
This paper enhances the initial muon track reconstruction in IceCube by applying robust statistical methods, resulting in a 13% improvement in directional accuracy and 98% accuracy in counting muons in coincident events.
Contribution
The work introduces robust statistical techniques into early-stage reconstruction, significantly improving accuracy without complex physical modeling.
Findings
13% improvement in median angular resolution
98% accuracy in determining the number of muons
Enhanced early reconstruction for subsequent analysis
Abstract
The IceCube project has transformed one cubic kilometer of deep natural Antarctic ice into a Cherenkov detector. Muon neutrinos are detected and their direction inferred by mapping the light produced by the secondary muon track inside the volume instrumented with photomultipliers. Reconstructing the muon track from the observed light is challenging due to noise, light scattering in the ice medium, and the possibility of simultaneously having multiple muons inside the detector, resulting from the large flux of cosmic ray muons. This manuscript describes work on two problems: (1) the track reconstruction problem, in which, given a set of observations, the goal is to recover the track of a muon; and (2) the coincident event problem, which is to determine how many muons are active in the detector during a time window. Rather than solving these problems by developing more complex physical…
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