Machine Learning for Jet Physics

Deep(Boosted)Jet: Boosted jet identification using particle-level convolutional neural networks (15'+5')

11 Dec 2017, 13:30

20m

2-100 (Lawrence Berkeley National Laboratory)

Jet tagging

Speaker

Qu Huilin (UCSB)

Description

dentification of boosted top quarks from their hadronic decays can play an important role in searches for new physics at the LHC. We present DeepBoostedJet, a new approach for boosted jet identification using particle-flow jets at CMS. One dimensional convolutional neural networks are utilized to classify a jet directly from its reconstructed constituent particles. The new method shows significant improvement in performance compared to alternative multivariate methods using jet-level observables.

Presentation materials

Slides

boosted_jet_tagging_p-cnn_hqu_20171211.pdf