Bayesian Study of Jet Background Subtraction in Relativistic Heavy-Ion Collisions

Jets are an essential probe to study the microscopic properties of the quark gluon plasma created in relativistic heavy ion collisions, however studies of jet observables can depend upon background subtraction methods and inputs.  In order to study these effects we have developed a simple model by embedding scaled pythia jets into a thermal blast-wave generated background distribution with event multiplicities and eccentricities generated by the TRENTO model.  We apply a background subtraction method developed by ATLAS to jets identified using the FASTJET package, and we investigate the sensitivity to jet-finding and background subtraction using a kernel density estimator in a Bayesian approach to search for biases in the determination of the pythia scaling factor.  Results are reported for several different event centrality ranges and background subtraction inputs.