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PKDD
2015
Springer

Discovering Neutrinos Through Data Analytics

7 years 11 months ago
Discovering Neutrinos Through Data Analytics
Abstract. Astrophysical experiments produce Big Data which need efficient and e↵ective data analytics. In this paper we present a general data analysis process which has been successfully applied to data from IceCube, a cubic kilometer neutrino detector located at the geographic South Pole. The goal of the analysis is to separate neutrinos from atmospheric muons within the data to determine the muon neutrino energy spectrum. The presented process covers straight cuts, variable selection, classification, and unfolding. A major challenge in the separation is the unbalanced dataset. The expected signal to background ratio in the initial data (trigger level) is roughly 1:106 . The overall process was embedded in a multi-fold cross-validation to control its performance. A subsequent regularized unfolding yields the sought after neutrino energy spectrum.
Mathis Börner, Wolfgang Rhode, Tim Ruhe, Kath
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where PKDD
Authors Mathis Börner, Wolfgang Rhode, Tim Ruhe, Katharina Morik
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