Speaker
Description
The ICARUS T600 Liquid Argon Time Projection Chamber (LArTPC) detector is the far detector of the Short Baseline Neutrino (SBN) Program located at Fermilab National Laboratory (FNAL). The data collection for ICARUS began in May 2021, utilizing neutrinos from the Booster Neutrino Beam (BNB) and the Neutrinos at the Main Injector off-axis beam (NuMI). The SBN Program has been designed to investigate the observed neutrino anomalies e.g. the former electron neutrino excess from the LSND experiment and the more recent MiniBooNE anomaly. To analyze collected neutrino data, we utilize two methods of event reconstruction: (1) the Pandora multi-algorithm approach to automated pattern recognition, and (2) an approach making use of machine learning (ML). The latter of two reconstruction methods folds in 3D voxel-level feature extraction using sparse convolutional neural networks and particle clustering using graph neural networks to produce outputs suitable for physics analyses. This presentation will summarize the performance of a high-purity and high-efficiency end-to-end machine learning-based selection of muon neutrinos from the BNB and highlight studies of electromagnetic shower reconstruction from a neutral pion selection.
