Speaker
Congqiao Li
(Peking University (CN))
Description
This talk summarizes recent progress in boosted object tagging in the CMS experiment, focusing on developments targeting Run 3 analyses. Updates to deep learning–based taggers are presented, including improvements in training strategies, input representations, and robustness to pileup and detector effects. Advances in calibration and systematic uncertainty evaluation are discussed, with emphasis on high-pT regimes. A dedicated focus is given to boosted tau identification, including adaptations of DeepTau-like approaches to collimated decay topologies. Their performance is evaluated in terms of efficiency and background rejection, and compared to standard resolved tau reconstruction.
Author
Congqiao Li
(Peking University (CN))