Speaker
Michele Selvaggi
(CERN)
Description
Identification of the flavour of the parton that originated the jet is of paramount importance for the FCC-ee program. The observables that allow to discriminate between different jet flavours such as track displacements and time-of-flight are introduced together with the detector design choices that are required to optimally reconstruct such variables. Jet flavour discriminators built on state-of-the-art Machine Learning (ML) techniques using graph-based neutral networks are then described, and the impact of different detector design assumptions on the performance is discussed. The application on the measurement of the charm and strange yukawa is then briefly discussed.
Author
Michele Selvaggi
(CERN)
