Speaker
Jae Jin Hong
(Indiana University (US))
Description
Discriminating highly boosted jets from the decays of heavy scalar particles that do not involve b-quarks from background is a very challenging problem. We describe a novel "4-Prong Tagger" that uses a graph neural network based on the Lund Jet Planes of a large radius jet to distinguish high energy scalar particle decays, S->WW->4q, from backgrounds such as QCD, hadronic vector-boson decays, and hadronic top decays. We show that this tagger can provide substantial sensitivity gains with respect to other jet sub-structure-based discriminants using a simple example analysis. We also discuss techniques for calibrating the 4-Prong Tagger using the Lund Jet Planes of the subjets of the top and vector boson control samples.
Author
Jae Jin Hong
(Indiana University (US))