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Jet-Images: Computer Vision Inspired Techniques for Jet Tagging

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arxiv 1407.5675 v3 pith:RRSW3FQ3 submitted 2014-07-21 hep-ph hep-exphysics.data-an

classification hep-phhep-exphysics.data-an
keywords jet-imagecomputerdiscriminantinspiredjet-imagesjetstaggingtechnique
verification ladder T0 review T1 audit T2 compute T3 formal
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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 gluon- initiated 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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Dynamics of Hot QCD Matter 2024 -- Hard Probes

    nucl-ex 2024-12 conditional novelty 4.0 of 10

    Proceedings volume summarizing hard probe studies of quark-gluon plasma, with preliminary new results on non-Markovian quarkonium evolution, jet transport simulations, and machine learning taggers.

  2. Transformer networks for Heavy flavor jet tagging

    hep-ph 2024-11 conditional novelty 2.0 of 10

    A review of transformer-based jet tagging that highlights the authors' CA-Mixer network as a state-of-the-art, faster alternative to Particle Transformer.

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