EP-IT Data Science Seminars

Jet flavour identification using Graph Neural Networks in CMS

by Loukas Gouskos (CERN)

Europe/Zurich
40/S2-B01 - Salle Bohr (CERN)

40/S2-B01 - Salle Bohr

CERN

100
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Description

The identification of the flavour of the parton that initiated the spray of stable particles forming a jet is a fundamental component of standard model measurements and searches for new physics with quarks and gluons in the final state. The first jet identification algorithms were developed using classical methods, however since the beginning of LHC Run 2 the development of significantly more advanced methods, making use of machine learning techniques, led to substantial improvement in performance, and hence in the physics reach. Particularly, Graph Neural Networks (GNNs) are emerging as an extremely powerful class of architectures; GNNs provide a much more natural representation for many tasks in High Energy Physics, including the task of jet identification. In today's seminar we will present a new generation of jet identification algorithms developed by CMS, which exploit customised GNNs tailored to the jet identification task, yielding a drastic improvement in performance compared to previous algorithms. 

Loukas Gouskos is a staff researcher at CERN working on the CMS experiment. He received his Ph.D. from the University of Athens. His research interests are focused on the search for physics beyond the standard model and the measurement of the Higgs boson properties. Loukas has a prominent role in searches for supersymmetric partners of the top quark, for Higgs boson decays to a pair of charm quarks, and for Higgs boson pair production in the high-momentum regime. In parallel, Loukas has been deeply involved in the developments in missing transverse momentum reconstruction and in jet tagging particularly with novel machine-learning-based algorithms. Lastly, he is active in the CMS Phase 2 program, focusing on the upgrade of the endcap calorimeters with the High Granularity Calorimeter.

Coffee will be served at 10h30.

Organized by

M. Girone, M. Elsing, L. Moneta, M. Pierini

Videoconference
EP/IT Data Science Seminar
Zoom Meeting ID
98545267593
Description
EP/IT Data Science seminar
Host
Lorenzo Moneta
Alternative hosts
Markus Elsing, EP Seminars and Colloquia, Maurizio Pierini, Caroline Cazenoves, Maria Girone
Passcode
97200142
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