Orateur
Sofia Palacios Schweitzer
(ITP, Heidelberg University)
Description
Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We show how a generative diffusion network learns off-shell kinematics given the much simpler on-shell process. It generates off-shell configurations fast and precisely, while reproducing even challenging on-shell features.
Auteurs principaux
Anja Butter
(LPNHE)
Mathias Kuschick
(Universität Münster)
Michael Klasen
(LPSC)
Sofia Palacios Schweitzer
(ITP, Heidelberg University)
Tilman Plehn
(Heidelberg University)
Tomas Jezo
(LPSC)
