Using Kinematics to Identify Quarks and Gluons in Final Dijet States

Quarks and gluons produced in the LHC rapidly fragment into groupings of collinear particles referred to as jets. Quark-initiated and gluon-initiated jets leave similar signatures in the ATLAS detector. Improving the classification of jets has a variety of useful applications such as studies on jet substructure and in searches for physics beyond the standard model. A boosted decision tree classifier was trained using the Toolkit for Multivariate Analysis to identify quark leading jets in dijet events based on the event kinematics along with the subleading jet's mass. Evaluation of the kinematic jet classifier shows best performance at high η values and in the leading jet transverse momentum range of 1.5 TeV to 2.5 TeV. A kinematic-based jet classifier will provide useful samples from real collision data that can be used in the training and validation of jet substructure-based taggers.