Aachen 2019 – scientific programme

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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 3: Machine-learning methods and computing in astroparticle physics

AKPIK 3.2: Talk

Wednesday, March 27, 2019, 16:10–16:20, H06

Possible ways to improve the DeepCore NMO analysis — •Jan Weldert and Sebastian Böser for the IceCube collaboration — JGU, Mainz, Germany

The neutrino mass ordering (NMO) is one of the driving questions in the field of neutrino physics. The NMO sensitivity potential of atmospheric neutrino detectors like the IceCube low energy extension DeepCore is limited by the achievable resolutions.
Two of the most promising ways to increase the DeepCore NMO sensitivity are:

1. 1) Relaxing the background cuts to increase the number of events considered in the analysis
2. 2) A better classification of the different event types (current track-like and cascade-like events).

While improvements in both of these are likely computationally expensive, the analysis of future detectors/detector upgrades will also benefit from advances made for current detectors.
This talk will discuss the potential of these improvements and possible ways to realize them, especially focusing on the application of neural networks to classify low energetic DeepCore events.