Determining the Size of Quark and Gluon Jets in CMS Open Data

The complex substructure of jets produced in proton-proton collisions at the Large Hadron Collider (LHC) is one of the keys to probe new physics. However, the shape and the size of jets are not fully understood. The focus of this study is to fit quark and gluon jets from CMS Open Data collected in 2011 into various shapes defined by the SHAPER optimal transport framework and determine the radii distributions of each shape. We first analyze the radii distributions in the dataset based on theoretical predictions and a simulation of the CMS detector. In processing the real data, a classifier is trained using the EnergyFlow machine learning framework to distinguish quark and gluon jets. The radii distributions in real data are then analyzed and compared with the simulation data. The results are the first analysis of the size of jets under this framework, which provides further insight into the jet substructure and can potentially expand our understanding of quantum chromodynamics.