Maximum Likelihood Reconstruction of Water Cherenkov Events With Deep Generative Neural Networks

Maximum Likelihood Reconstruction of Water Cherenkov Events With Deep Generative Neural Networks

Large water Cherenkov detectors have shaped our current knowledge of neutrino physics and nucleon decay, and will continue to do so in the foreseeable future. These highly capable detectors allow for directional and topological, as well as calorimetric information to be extracted from signals on the...

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Bibliographic Details
Main Authors: Mo Jia, Karan Kumar, Liam S. Mackey, Alexander Putra, Cristovao Vilela, Michael J. Wilking, Junjie Xia, Chiaki Yanagisawa, Karan Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Big Data
Subjects:
experimental particle physics
event reconstruction
water Cherenkov detectors
generative models
convolutional neural network
Online Access:https://www.frontiersin.org/articles/10.3389/fdata.2022.868333/full

Internet

https://www.frontiersin.org/articles/10.3389/fdata.2022.868333/full

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