Nov 25 – 27, 2019
DESY Hamburg
Europe/Berlin timezone

Attention-based reconstruction for ttH(bb) in CMS

Nov 26, 2019, 3:10 PM
SR 1 (DESY Hamburg)

SR 1

DESY Hamburg


Tobias Lösche (University of Hamburg)


A precise determination of the interactions of the Higgs boson with other SM particles is a crucial part of the LHC physics program. When determining the top Yukawa coupling in ttH(bb) events, deep learning plays an integral role. In the single-lepton channel, multivariate approaches using deep neural networks (DNNs) achieve state-of-the-art performance in signal/background classification. A particular challenge of this analysis is the discrimination of ttH(bb) events from the irreducible tt + bb background. Considering the combinatorial assignment of jets offers a possible means to deal with this problem and thus further improve performance. To achieve this, an attention-based DNN classifier (COBRA) was developed, whose results are presented in this talk.

Primary authors

Gregor Kasieczka (Institut fuer Experimentalphysik / UHH) Tobias Lösche (University of Hamburg)

Presentation materials