Charged-current neutrino-induced K+ production in MicroBooNE

MicroBooNE is an 85-ton active mass liquid-argon time projection chamber (LArTPC) neutrino detector exposed to the Booster Neutrino Beam (BNB) at Fermilab. MicroBooNE’s physics goals are the precision measurement of neutrino interactions on argon in the 1 GeV energy regime and investigating the Low Energy Excess (LEE) of neutrino events observed by the MiniBooNE experiment. The study of neutrino interactions producing a K$+$ in the final-state, which has never been measured on argon, can improve the background estimates for future proton-decay experiments looking for the p $\rightarrow$ K$+\nu$ channel on argon such as DUNE. In this work, we present a simulation study for a selection of associated K$+$ produced by charged-current neutrino interactions which decay into a $\mu+$ and a $\nu_\mu$ in the MicroBooNE detector. We will compare two different approaches to identify kaon tracks. The first approach uses calorimetry and the Bethe-Bloch prediction for various particle hypotheses, and the second approach uses machine learning techniques.