Titlebook: Domain Generalization with Machine Learning in the NOvA Experiment; Andrew T.C. Sutton Book 2023 The Editor(s) (if applicable) and The Aut

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https://doi.org/10.1007/978-3-319-30552-3either electon or tau-type neutrinos. The NOvA experiment, being composed of materials with a low atomic number, was designed to efficiently detect both the muons and electrons that accompany a charge-current neutrino interaction.

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Pam Denbesten,Robert Faller,Yukiko Nakano particles, and apply machine learning techniques to determine their specific types. Finally, in order to perform our physics analyses, we must estimate the energies associated with each particle and interaction.

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Event Reconstruction, particles, and apply machine learning techniques to determine their specific types. Finally, in order to perform our physics analyses, we must estimate the energies associated with each particle and interaction.

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Book 2023orks (NN) can be used to identify the particle types or determine their energies in detectors such as those used in the NOvA neutrino experiment, which studies changes in a beam of neutrinos as it propagates approximately 800 km through the earth. NOvA relies heavily on simulations of the physics pr

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Domain Generalization with Machine Learning in the NOvA Experiment