Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber
2017
We present several studies of
convolutional neural networksapplied to data coming from the MicroBooNE detector, a liquid argon
time projection chamber(LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of
convolutional neural networksfor
particle identificationor event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.
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