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T: Fachverband Teilchenphysik

T 71: Data analysis, Information technology III

T 71.5: Vortrag

Mittwoch, 17. März 2021, 17:00–17:15, Tu

Charm jet identification and discriminator calibration with the CMS experiment — •Spandan Mondal¹, Xavier Coubez^1,2, Alena Dodonova¹, Luca Mastrolorenzo¹, Andrzej Novak¹, Andrey Pozdnyakov¹, and Alexander Schmidt¹ — ¹RWTH Aachen University, Germany — ²Brown University, USA

Identification of charm-quark-initiated jets at the LHC is especially challenging. Over the past few years, usage of advanced deep learning based algorithms has enabled several CMS analyses to efficiently discriminate charm jets simultaneously from bottom and light jets. The charm probability scores yielded by such charm tagging algorithms can play a powerful role when used as inputs to a machine learning based signal-background discriminating algorithm. However, as jet identification algorithms are trained strictly on simulated jets, a direct usage of charm tagger output values requires calibrating the entire output probability distributions using real jets reconstructed from CMS data. This talk focuses on charm jet identification algorithms in CMS as well as the calibration of their output discriminator values using flavour-enriched selections of jets in data.