Speaker
Javier Mariño Villadamigo
(Institut für Theoretische Physik - University of Heidelberg)
Description
Direct simulation of multi-parton QCD processes at full-color accuracy is computationally expensive, making it often impractical for large-scale LHC studies. A two-step approach has recently been proposed to address this: events are first generated using a fast leading-color approximation and reweighted to full-color accuracy. We build upon this strategy by introducing a machine-learning algorithm that learns the reweighting function directly. This enables us to retain the fast generation of approximate events while accelerating the costly reweighting step.
Authors
Javier Mariño Villadamigo
(Institut für Theoretische Physik - University of Heidelberg)
Olivier Mattelaer
(UCLouvain)
Ramon Winterhalder
(Università degli Studi di Milano)
Rikkert Frederix
(Lund University)
Tilman Plehn
(Heidelberg University)
Timea Vitos