Using machine learning to separate hadronic and electromagnetic interactions in the GlueX forward calorimeter

@article{Barsotti2020UsingML,
  title={Using machine learning to separate hadronic and electromagnetic interactions in the GlueX forward calorimeter},
  author={R. Barsotti and Matthew R. Shepherd},
  journal={arXiv: Data Analysis, Statistics and Probability},
  year={2020}
}
The GlueX forward calorimeter is an array of 2800 lead glass modules that was constructed to detect photons produced in the decays of hadrons. A background to this process originates from hadronic interactions in the calorimeter, which, in some instances, can be difficult to distinguish from low energy photon interactions. Machine learning techniques were applied to the classification of particle interactions in the GlueX forward calorimeter. The algorithms were trained on data using decays of… 
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