Speaker
Federica Primavera
(Universita e INFN, Bologna (IT))
Description
Muon objects play a key role in the CMS physics program, as many are the analyses targeting final state with muons. The ability to trigger, reconstruct, and identify events with prompt and non-prompt muons with high efficiency and excellent resolution is thus crucial for the success of the experiment. In this talk, muon reconstruction, identification and isolation efficiencies as well as momentum measurements during the first years of Run 3 of the LHC will be discussed. It will highlight novel machine learning algorithms used in High Level Trigger (HLT) and for muon identification.
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