Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data

@article{Drielsma2020ClusteringOE,
  title={Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data},
  author={Francois Drielsma and Qing Lin and Pierre Cote de Soux and Laura Domin'e and Ran Itay and Dae Heun Koh and Bradley J. Nelson and Kazuhiro Terao and Ka Vang Tsang and Tracy Usher},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.01335}
}
Liquid Argon Time Projection Chambers (LArTPCs) are a class of detectors that produce high resolution images of charged particles within their sensitive volume. In these images, the clustering of distinct particles into superstructures is of central importance to the current and future neutrino physics program. Electromagnetic (EM) activity typically exhibits spatially detached fragments of varying morphology and orientation that are challenging to efficiently assemble using traditional… 

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