Chasing top quarks and Higgs bosons with Artificial Intelligence

The LHCb collaboration has published two papers reporting the use of artificial intelligence in the study of top quark and Higgs boson production. The work examines decays of these particles into lighter quarks that fragment into jets of other particles. Such jets are difficult to measure precisely amid the high density of particles produced in proton-proton collisions at the Large Hadron Collider. Machine learning methods based on deep neural networks have supported analysis of these jets in the forward region covered by the LHCb detector. The papers present differential cross-section measurements for top quark and anti-top quark decays as a function of muon pseudorapidity. They also include a measurement of the top quark charge asymmetry derived from decays containing a muon and a b-jet. The same techniques have improved reconstruction of the Higgs boson decay into two quarks. The results position LHCb to pursue further measurements of Higgs boson properties during the High-Luminosity phase of the LHC.