Deep-learned top tagging with a Lorentz layer
We introduce a new and highly efficient tagger for hadronically decaying top quarks, based on a deep neural network working with Lorentz vectors and the Minkowski metric. With its novel machine learning setup and architecture it allows us to identify boosted top quarks not only from calorimeter towe...
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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) Kapitel/Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
27 Jul 2017
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| In: |
Arxiv
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| Online-Zugang: | Verlag, kostenfrei, Volltext: http://arxiv.org/abs/1707.08966
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| Verfasserangaben: | Anja Butter, Gregor Kasieczka, Tilman Plehn, and Michael Russell |
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