Speaker
Description
The Deep Underground Neutrino Experiment will operate large-scale Liquid-Argon Time-Projection Chambers at the far site in South Dakota, producing high-resolution images of neutrino interactions. Extracting the maximum value from the images requires sophisticated pattern-recognition to interpret detector signals as physically meaningful objects for physics analyses. Identifying the neutrino interaction vertex is critical because subsequent algorithms depend on this to identify and separate individual primary particles. In this talk I will present a UNet within the Pandora pattern-recognition framework for identifying the interaction vertex and look at the robustness of the network to input variations motivated by alternative nuclear models.
| Type of contribution | Talk: 15 minutes. |
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