Spectral analysis of jet substructure with neural networks: boosted Higgs case

@article{Lim2018SpectralAO,
  title={Spectral analysis of jet substructure with neural networks: boosted Higgs case},
  author={Sung Hak Lim and Mihoko M. Nojiri},
  journal={Journal of High Energy Physics},
  year={2018},
  volume={2018},
  pages={1-20}
}
A bstractJets from boosted heavy particles have a typical angular scale which can be used to distinguish them from QCD jets. We introduce a machine learning strategy for jet substructure analysis using a spectral function on the angular scale. The angular spectrum allows us to scan energy deposits over the angle between a pair of particles in a highly visual way. We set up an artificial neural network (ANN) to find out characteristic shapes of the spectra of the jets from heavy particle decays… 

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