Heidelberg 2022 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 35: Higgs Boson: Associated Production 1

T 35.6: Vortrag

Dienstag, 22. März 2022, 17:30–17:45, T-H20

Performance Tests of tH(bb) Signal and Background Separation Using a Binary Classifier Neural Network with ATLAS Data — Igor Boyko¹, Nazim Huseynov¹, Oksana Koval¹, •Marcel Patzwahl², and André Sopczak² — ¹JINR Dubna — ²CTU in Prague

The production of a Higgs boson in association with a single top quark is a strongly suppressed process in the Standard Model (SM). In the current ATLAS data set of 140 fb⁻¹, the SM expected production rate is below the experimental sensitivity. Thus, observing such a tH production would indicate new physics. The absolute ttH coupling strength was already measured and the tH process can in addition measure the relative sign of the ttH coupling. Therefore, observing the tH process gives an important additional insight into the physics of the Higgs mechanism. Owing to the low production rate, it is particularly important to enhance the signal sensitivity, and a Neural Network (NN) is used. The resulting significance is studied by varying the NN structure. Based on simulated data, the performances of these different NN structures were tested and results are expressed as area under the ROC curve to quantify the signal and background separation.