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NOvA is a long-baseline neutrino oscillation experiment. It uses the NuMIbeam from Fermilab and two sampling calorimeter detectors placed off-axis fromthe beam. The 293 ton Near Detector measures the unoscillated neutrino energyspectrum, which can be used to predict the neutrino energy spectrum observed atthe 14 kton Far Detector. The Near Detector also provides an excellentopportunity to measure neutrino interaction cross sections with highstatistics, which will benefit current and future long-baseline neutrinooscillation experiments. This analysis implements new algorithms to identify$\nu_{\mu}$ charge-current events by using visual deep learning tools such asconvolutional neural networks. We present the status of a measurement of theinclusive $\nu_{\mu}$ CC cross section in the NOvA Near Detector.

Status of a Deep Learning Based Measurement of the Inclusive Muon Neutrino Charged-current Cross Section in the NOvA Near Detector