Abstract
We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current interactions with final state s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (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 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of kinematics.
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