Heidelberg 2022 – scientific programme

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T: Fachverband Teilchenphysik

T 7: Top Quarks: Properties 1

T 7.4: Talk

Monday, March 21, 2022, 17:00–17:15, T-H20

Neural network based estimators to measure the top quark mass — Christoph Garbers, Johannes Lange, •Nathan Prouvost, Peter Schleper, and Hartmut Stadie — Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg

The top quark is the heaviest known particle in the Standard Model. As such, the top quark mass is an important parameter for constraining and checking the validity of Standard Model predictions. In the semi-leptonic decay channel, a value of the top quark mass of 172.25±0.63 GeV has been measured with 35 fb⁻¹ of the 2016 data at the CMS experiment. The mass of the top quark from a kinematic fit and the reconstructed mass of the W boson are used as variables. It is expected that adding more variables will improve the measurement. This presentation focuses on the development of neural network based estimators of the top quark mass using nuisance parameters for the systematics and multiple observables.