Supervised ML classification of neutrino events by interaction channel prior to energy reconstruction improves accuracy and sensitivity by 10-20% in simulated DUNE analyses while remaining robust to generator mismodeling.
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Hybrid HF-CRPA calculations predict lower allowed cross sections for charged-current ν_e on 40Ar at low energies, leading to ~20% fewer events in DUNE for a galactic supernova burst than the prior MARLEY model.
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Improving Neutrino Oscillation Measurements through Event Classification
Supervised ML classification of neutrino events by interaction channel prior to energy reconstruction improves accuracy and sensitivity by 10-20% in simulated DUNE analyses while remaining robust to generator mismodeling.