Speaker
Linyan Wan
(Fermilab)
Description
Neutrino public datasets are increasingly important for advancing neutrino physics by broadening participation, enabling independent cross-checks, and supporting method development beyond large experimental collaborations. However, their scientific utility is limited when users lack access to detector simulation or the detailed detector knowledge needed to interpret reconstructed quantities. We propose to address this gap by building a surrogate model of detector response for neutrino public data. The goal is to construct an uncertainty-aware bidirectional model that maps between simulated particles and reconstructed particles in both directions. This work reports the current progress on the project.
| Contribution types | Short talk (15min + 5min Q/A) |
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