Orateur
Nathan Huetsch
(Heidelberg University)
Description
The matrix element method is the LHC inference method of choice for limited statistics.
We present a dedicated machine learning framework, based on efficient phase-space
integration, a learned acceptance and transfer function. It is based on a choice of INN
and diffusion networks, and a transformer to solve jet combinatorics. Bayesian networks allow us to capture network uncertainties, bootstrapping allows us to estimate integration uncertainties. We showcase this setup for the CP-phase of the top Yukawa coupling in associated Higgs and single-top production.
Paper: arXiv:2310.07752
Auteurs principaux
Anja Butter
(LPNHE)
Nathan Huetsch
(Heidelberg University)
Ramon Winterhalder
(UC Louvain)
Theo Heimel
(Heidelberg University)
Tilman Plehn
(Heidelberg University)
