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June 22, 2020 to July 2, 2020
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Selection Of Muon Neutrinos for the MicroBooNE Deep-Learning-based Low Energy Excess Search

Not scheduled
10m

Speaker

Davio Cianci

Description

MicroBooNE is a liquid argon time projection chamber (LArTPC) detector positioned on the Fermilab booster beamline whose primary goal is to verify an excess of low energy electron neutrinos observed by MiniBooNE on the same beam. To this end, a reliable measurement of muon neutrinos in parallel with one of electron neutrinos can provide a constraint on systematic uncertainties, strengthening any claims about the anomalous low energy excess (LEE).

This poster presents a selection of muon neutrino events identified as having one muon and one proton in the final state in the MicroBooNE experiment pairing cutting edge deep-learning-based track reconstruction methods with the fine topological resolution provided by LArTPC detector technology.

Mini-abstract

Using Deep Learning tools to select muon neutrinos for the MicroBooNE Low Energy Excess Search.

Experiment/Collaboration MicroBooNE

Primary author

Presentation Materials