Edmund Witkowski

Nov 17, 2023 | link.aps.org | Edmund Witkowski |Benjamin Nachman |Daniel Whiteson

Abstract We use unlabeled collision data and weakly supervised learning to train models that can distinguish prompt muons from nonprompt muons using patterns of low-level particle activity in the vicinity of the muon and interpret the models in the space of energy flow polynomials. Particle activity associated with muons is a valuable tool for identifying prompt muons, those due to heavy boson decay, from muons produced in the decay of heavy flavor jets.