Reconstruction and Measurement of $\mathcal{O}$(100) MeV Energy Electromagnetic Activity from $\pi^0 \rightarrow \gamma\gamma$ Decays in the MicroBooNE LArTPC

TL;DR

This paper develops an automated method combining traditional and machine learning techniques to reconstruct and measure electromagnetic activity from photon decays in neutrino interactions within the MicroBooNE liquid argon TPC, achieving good resolution and data-simulation agreement.

Contribution

It introduces a novel automated reconstruction chain for low-energy electromagnetic showers in a liquid argon detector, integrating machine learning for improved identification and measurement.

Findings

Good energy resolution for ~100 MeV EM showers

Strong agreement between data and simulation

Demonstrated potential for photon-electron separation

Abstract

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current $\nu_{\mu}$ interactions with final state $\pi^0$s. We employ a fully-automated reconstruction chain capable of identifying EM showers of $\mathcal{O}$(100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant $\pi^0$ mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of $\nu_{\mu} + {\rm Ar} \rightarrow \mu + \pi^0 + X$ candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of $\pi^0$ kinematics.