Speaker
Description
The NOvA experiment is a long-baseline accelerator neutrino experiment utilizing Fermilab's upgraded NuMI beam. It measures the appearance of electron neutrinos and the disappearance of muon neutrinos at its Far Detector in Ash River, Minnesota. NOvA is the first neutrino experiment to use convolutional neural networks (CNNs) for event identification and reconstruction. Recently, we introduced a transformer network—commonly used in large language models like ChatGPT—for simultaneous event classification and final state particle identification at NOvA. This neural network also incorporates Sparse CNNs into its architecture. The attention mechanism in the transformer is used to diagnose the neural network and study correlations between inputs and outputs, thereby providing interpretability to the neural network. In this talk, I will discuss the architecture, identification performance, and interpretability of the NOvA transformer neural network.
| Type of contribution | Talk: 15 minutes. |
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