9-12 April 2018
CERN
Europe/Zurich timezone
There is a live webcast for this event.

DeepJet: a deep-learned multiclass jet-tagger for slim and fat jets

9 Apr 2018, 11:00
20m
500-1-001 - Main Auditorium (CERN)

500-1-001 - Main Auditorium

CERN

400
Show room on map

Speakers

Mauro Verzetti (CERN) Jan Kieseler (CERN) Markus Stoye (CERN) Huilin Qu (Univ. of California Santa Barbara (US)) Loukas Gouskos (Univ. of California Santa Barbara (US))

Description

We present a customized neural network architecture for both, slim and fat jet tagging. It is based on the idea to keep the concept of physics objects, like particle flow particles, as a core element of the network architecture. The deep learning algorithm works for most of the common jet classes, i.e. b, c, usd and gluon jets for slim jets and W, Z, H, QCD and top classes for fat jets. The developed architecture promising gains in performance as shown in simulation of the CMS collaboration. Currently the tagger is under test in real data in the CMS experiment.

Intended contribution length 20 minutes

Primary authors

Mauro Verzetti (CERN) Jan Kieseler (CERN) Markus Stoye (CERN) Huilin Qu (Univ. of California Santa Barbara (US)) Loukas Gouskos (Univ. of California Santa Barbara (US))

Presentation Materials

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