Heidelberg 2022 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 26: Data Analysis, Information Technology and Artificial Intelligence

T 26.4: Vortrag

Montag, 21. März 2022, 17:00–17:15, T-H39

Reduction of the Irreducible Background in the ttH(bb) Analysis at ATLAS, Using a Deep-Sets-Based bb-Tagger — •Joschka Birk, Alexander Froch, and Andrea Knue — Albert-Ludwigs-Universität Freiburg

The search for the ttH(bb) signal suffers from the large irreducible tt+bb background. This irreducible background contains the same final-state particles as the signal, including four b quarks. In the background process, a radiated gluon can split into a b-quark pair, which often leads to two b-jets that are very close together. With the currently used b-tagging algorithm, these bb-jets are often misidentified as a single b-jet.
In order to improve the rejection of these background events, the existing Deep-Impact-Parameter-Sets (DIPS) Tagger is extended with an additional output class dedicated to jets which contain two b-hadrons (bb-jets). DIPS is part of a new ATLAS b-tagging algorithm, based on the Deep Sets architecture, and has already shown promising performance compared to the RNNIP tagger, which is part of the DL1r tagger that is currently used in ATLAS analyses. Studies of this extended version of the DIPS tagger, including first results of a hyperparameter optimisation, are presented.