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Low energy event reconstruction in IceCube DeepCore

Author(s)
Abbasi, R.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Ahrens, M.; Alameddine, J. M.; Alves, A. A.; Amin, N. M.; Andeen, K.; Anderson, T.; Anton, G.; Argüelles, C.; Ashida, Y.; Axani, S.; Bai, X.; V., A. B.; Barwick, S. W.; Bastian, B.; Basu, V.; ... Show more Show less
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Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/
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Abstract
Abstract The reconstruction of event-level information, such as the direction or energy of a neutrino interacting in IceCube DeepCore, is a crucial ingredient to many physics analyses. Algorithms to extract this high level information from the detector’s raw data have been successfully developed and used for high energy events. In this work, we address unique challenges associated with the reconstruction of lower energy events in the range of a few to hundreds of GeV and present two separate, state-of-the-art algorithms. One algorithm focuses on the fast directional reconstruction of events based on unscattered light. The second algorithm is a likelihood-based multipurpose reconstruction offering superior resolutions, at the expense of larger computational cost.
Date issued
2022-09-09
URI
https://hdl.handle.net/1721.1/145345
Department
Massachusetts Institute of Technology. Department of Physics
Publisher
Springer Berlin Heidelberg
Citation
The European Physical Journal C. 2022 Sep 09;82(9):807
Version: Final published version

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