Speaker
Joaquin Iturriza Ramirez
(LPNHE - Sorbonne Université)
Description
Fast and precise evaluations of scattering amplitudes even in the case of precision calculations is essential for event generation tools at the HL-LHC. We explore the scaling behavior of the achievable precision of neural networks in this regression problem for multiple architectures, including a Lorentz symmetry aware multilayer perceptron and a fully Lorentz equivariant transformer using Lorentz Local Canonicalization (LLoCa). This study addresses in particular the scaling behavior of uncertainty estimations using state of the art methods.
Authors
Anja Butter
(LPNHE, Sorbonne Université, Université Paris Cité, CNRS/IN2P3, Paris, France, Institut für Theoretische Physik, Universität Heidelberg, Germany)
Henning Bahl
Joaquin Iturriza Ramirez
(LPNHE - Sorbonne Université)
Victor Bresó-Pla