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We introduce an optimization technique to discriminate signal and backgroundin any phenomenological study based on the cut and count-based method. The coreideas behind this algorithm is the introduction of a ranking scheme that canquantitatively assess the relative importance of various observables involvedin a new physics process, and a more methodical way of choosing what cuts toimpose. The technique is an iterative process that works with the help of theMadAnalysis5 interface. Working in the context of a simple BSM scenario with aheavy Higgs boson that decays to four leptons via ZZ, we demonstrate howautomating the cut and count process in this specific way results in anenhanced discovery potential compared with the more traditional way of imposingcuts.

Optimizing The Cut And Count Method In Phenomenological Studies