Speaker
Nathan Huetsch
(Institut für Theoretische Physik, Universität Heidelberg)
Description
The matrix element method remains a crucial tool for LHC inference in scenarios with limited event data. We enhance our neural network-based framework, now dubbed MEMeNNto, by optimizing phase-space integration techniques and introducing an acceptance function. Additionally, employing new architectures, like transformer and diffusion models, allows us to better handle complex jet combinatorics associated with initial-state radiation (ISR). These improvements are showcased again through the CP-
violating phase of the top Yukawa coupling in associated Higgs and single-top production, underlining the enhanced capabilities of our revised approach.
Authors
Theo Heimel
(Heidelberg University)
Nathan Huetsch
(Institut für Theoretische Physik, Universität Heidelberg)
Ramon Winterhalder
(UC Louvain)
Tilman Plehn
Anja Butter
(Centre National de la Recherche Scientifique (FR))
