Advancing the CMS Level-1 Trigger: Jet Tagging with DeepSets at the HL-LHC

Abstract

At the High Luminosity LHC, selecting important physics processes such as (di-) Higgs production will be a high priority. The Phase-2 Upgrade of the CMS Level-1 Trigger will reconstruct particle candidates and use pileup mitigation for the 200 simultaneous proton-proton interactions. A fast cone algorithm will reconstruct jets from these particles, providing access to jet constituents for the first time. We introduce a new multi-class jet tagger with a small, quantized DeepSets neural network. The tagger, trained on a mix of simulated CMS events, predicts various hadronic and leptonic classes. We present the tagger, its performance, and its improvements for triggering on (di-) Higgs events.