Bonn 2020 – wissenschaftliches Programm
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T 42.2: Vortrag
Dienstag, 31. März 2020, 17:15–17:30, L-4.001
Charm jet identification and discriminator calibration with the CMS experiment — •Spandan Mondal1, Xavier Coubez1,2, Luca Mastrolorenzo1, Andrzej Novak1, Andrey Pozdnyakov1, and Alexander Schmidt1 — 1Physikalisches Institut III A, RWTH Aachen University — 2Brown University
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.