3 November 2021
Ecole de physique
Europe/Zurich timezone

Solving ttbar Combinatorics Using Graph Neural Networks

3 Nov 2021, 16:06
1m
Ecole de physique

Ecole de physique

Speaker

Lukas Ehrke

Description

Events with a $t\bar{t}$ pair can have up to six jets coming from the two top quarks. Assigning these jets correctly to the two quarks is challenging due to large combinatorics especially in the allhadronic final state. The correct assignment of these jets has several benefits. For instance, the kinematics of the top quarks can be determined. Several different methods already exist for reconstructing different ttbar final states, both with and without machine learning. The novelty of this approach is the insertion of helper nodes as the intermediate particles. These helper nodes can additionally be used to regress towards the true properties of the intermediate particles. The approach can be generalized to any sort of decay chain within a detector

Primary authors

Lukas Ehrke Tobias Golling (University of Geneva) Johnny Raine (Universite de Geneve (CH)) Manuel Guth (Université de Genève) Sebastian Pina-Otey (University of Geneva) Knut Zoch (Université de Genève (CH))

Presentation Materials