ITP|
|
WS21/22 – Abstract
Frederic Dreyer
(University of Oxford)
18.11.2021
Probing fundamental interactions at the LHC
I will introduce the Lund jet plane, a powerful representation of radiation patterns within a jet, and adopt this framework to explore our first-principles understanding of machine learning methods for LHC physics. I will then discuss limitations of existing dipole showers in accurately describing emissions across multiple energy scales, and show
how this can lead to bias in machine learning models. Finally, I will introduce systematic tools to assess the logarithmic accuracy of a parton shower and introduce two novel showers that can achieve next-to-leading logarithmic accuracy for a broad range of observables.
