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Learning from the Lund planeAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact . Lund diagrams, a theoretical representation of the phase space within jets, have long been used in discussing parton showers and resummations. I will show that they can be created for individual jets through repeated Cambridge/Aachen declustering, providing a powerful visual representation of the radiation within any given jet. Concentrating on the primary Lund plane, I will outline some of its analytical properties, highlight its scope for constraining Monte Carlo simulations and comment on its relation with existing observables. I will then examine its use for boosted electroweak boson tagging, showing that it can provide good performance when used as input to machine learning approaches or within a log-likelihood method. Finally, I will discuss applications to the issue of jet grooming, and introduce a framework to automate the definition of a jet grooming algorithm through the use of reinforcement learning, showing how the removal of soft wide-angle partons can be optimized by the RL agent through an appropriate choice of reward function. This talk is part of the Cavendish HEP Seminars series. This talk is included in these lists:
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