Heidelberg 2022 – scientific programme

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T: Fachverband Teilchenphysik

T 69: DAQ and Trigger 3

T 69.5: Talk

Wednesday, March 23, 2022, 17:15–17:30, T-H28

Development of machine-learning based topological selection algorithms for the upgraded L1 trigger system of the CMS detector — •Ihor Komarov, Johannes Haller, Finn Labe, Artur Lobanov, and Matthias Schröder — Institut für Experimentalphysik, Universität Hamburg

Future data-taking periods at the LHC bring a major increase of the instantaneous luminosity. To cope with the large detector occupancy within the bandwidth constraints, significant improvements of the trigger systems of the experiments are needed. The upgraded Level-1 trigger system of the CMS experiment will allow the execution of complex algorithms, such as neural networks, on field-programmable gate arrays (FPGAs).

In this talk, a first proof-of-concept study on fast neural-network-based selection algorithms for the L1 trigger system of CMS will be presented. The algorithms were benchmarked with top-quark and Higgs pair production signals. Preliminary results show significant performance improvements compared to existing algorithms.