Progress of the Charged Pion Semi-Inclusive Neutrino Charged Current Cross Section in NOvA

TL;DR

This paper reports on the progress of measuring the charged pion semi-inclusive neutrino charged current cross section in the NOvA experiment, utilizing neural network-based event classification to improve interaction identification.

Contribution

It introduces a convolutional neural network approach for identifying neutrino interactions with charged pions, enhancing analysis capabilities in neutrino cross section measurements.

Findings

Development of a CNN-based particle identification method

Assessment of systematic uncertainties in the measurement

Progress towards precise cross section measurement

Abstract

The NOvA experiment is a long-baseline neutrino oscillation experiment designed to measure the rates of electron neutrino appearance and muon neutrino disappearance. The NOvA near detector is located at Fermilab, 800 m from the primary target and provides an excellent platform to measure and study neutrino-nucleus interactions. We present the status of the measurement of the double differential cross section with respect to muon kinematics for interactions involving charged pions in the final state, $\nu_{\mu} + N \rightarrow \mu + \pi^{+/-} + X$. We have derived a convolutional neural network-based approach for the identification of neutrino interactions with the specific final state topology. We present event classification efficiency studies using this particle identification and classification methodology, along with systematic uncertainties and prospects for the measurement.