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Electromagnetic shower reconstruction and energy validation with Michel electrons and π<sup>0</sup> samples for the deep-learning-based analyses in MicroBooNE
This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of traditional and deep learning-based techniques to estimate shower energies. We validate these predictions using two $\nu_{\mu}$-sourced data samples: charged/neutral …