Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

Understand

We present several studies of convolutional neural networks applied 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 networks for particle identification or 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.