DUNE

The Deep Underground Neutrino Experiment (DUNE) will be the largest liquid argon detector ever built, and the best thing about it is its range: the same detector that records multi-GeV beam neutrinos can study atmospheric muons at hundreds of GeV and supernova neutrinos at a few MeV. My group works on the low-energy end of that range, developing advanced machine learning reconstruction techniques to lower DUNE’s energy threshold and expand what we can learn from low-energy interactions.

Past contributions to DUNE include phenomenology at high energy (~ 500 GeV) and low energy (~ 5 MeV) scales. Phys. Rev. D 104, 092015 explores DUNE’s high energy sensitivity to BSM scenarios with atmospheric neutrinos, and Phys. Rev. D 108, 043005 investigates DUNE’s sensitivity to the NuX component of galactic supernova neutrinos.

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Low-energy reconstruction and AI methods

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SIREN and multi-experiment inference