Bonn 2020 – scientific programme

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T: Fachverband Teilchenphysik

T 58: Higgs: associated production

T 58.9: Talk

Wednesday, April 1, 2020, 18:30–18:45, H-1.002

Improvement of the jet-parton assignment in ttH(bb) events using machine-learning techniques — •Felicia Volle, Andrea Knue, and Gregor Herten — Albert-Ludwigs-Universität Freiburg, Deutschland

The associated production of a Higgs boson and a top-antitop-quark pair allows to directly measure the Higgs-top Yukawa coupling, which can be sensitive to Beyond Standard Model physics. In the studies presented, a final state with the Higgs boson decaying into two b-quarks and the tt pair decaying into the lepton+jets channel is investigated. This decay channel suffers from irreducible tt+bb background. In order to discriminate signal from background, a good reconstruction of the signal event is of utmost importance.

In the targeted decay channel, at least six jets are expected to be present in the final state. Four of these jets are expected to originate from a b-hadron. Having that many jets in the final state, the correct assignment of the measured jets to their corresponding parton-level object proves difficult. A Boosted Decision Tree has been used in the past in order to identify the correct permutation. The performance of this Boosted Decision Tree is presented and first studies towards using a deep neural network for the assignment will be shown.