Neural Network Tagger for Single Higgs Boson that Decays into Two W Bosons

Although the experimental discovery of the Higgs boson by the Large Hadron Collider at CERN marked the completion of the standard model (SM), there are still many mysteries that the SM cannot explain and may require us to know more about the Higgs boson. Discriminating the Higgs boson from the background is the first step towards more precise measurements and better insights into the Higgs mechanism. One decay mode of the Higgs boson is the WW* mode, in which a Higgs boson decays into a pair of W bosons (HWW), which has been considered a difficult final state to analyze due to its low signal-to-background ratio. We adapt the ParticleNet deep graph neural network architecture to identify the HWW topology and tune the model and input selections. We have achieved so far an area under the receiver operating characteristic (ROC) curve (AUC) of 91.5% and the signal efficiency of about 40% at 1% background efficiency. Besides, the dependency of performance on the Higgs mass and transverse momentum has been largely reduced.