Separation of quark and gluon jets in the direct photon production processes at the LHC using the neural network approach
Abstract
A neural network technique is used to discriminate between quark and gluon jets produced in the qg->q+photon and q q->g+photon processes at the LHC. Considering the network as a trigger and using the PYTHIA event generator and the full event fast simulation package for the CMS detector CMSJET we obtain signal-to-background ratios.