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Journal of High Energy Physics

, 2015:118 | Cite as

Jet-images: computer vision inspired techniques for jet tagging

  • Josh Cogan
  • Michael KaganEmail author
  • Emanuel Strauss
  • Ariel Schwarztman
Open Access
Regular Article - Theoretical Physics

Abstract

We introduce a novel approach to jet tagging and classification through the use of techniques inspired by computer vision. Drawing parallels to the problem of facial recognition in images, we define a jet-image using calorimeter towers as the elements of the image and establish jet-image preprocessing methods. For the jet-image processing step, we develop a discriminant for classifying the jet-images derived using Fisher discriminant analysis. The effectiveness of the technique is shown within the context of identifying boosted hadronic W boson decays with respect to a background of quark- and gluoninitiated jets. Using Monte Carlo simulation, we demonstrate that the performance of this technique introduces additional discriminating power over other substructure approaches, and gives significant insight into the internal structure of jets.

Keywords

Jets Hadronic Colliders 

Notes

Open Access

This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.

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Copyright information

© The Author(s) 2015

Authors and Affiliations

  • Josh Cogan
    • 1
  • Michael Kagan
    • 1
    Email author
  • Emanuel Strauss
    • 1
  • Ariel Schwarztman
    • 1
  1. 1.SLAC National Accelerator LaboratoryMenlo ParkU.S.A.

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