An iterative ranking-based optimization of cut-and-count using MadAnalysis5 enhances signal-background separation and discovery reach for singly charged Higgs in the Two Higgs Doublet Model.
The suggested cuts on following the algorithm at each iteration are shown in Figure 7 and the final cut flow chart is shown in Table IV
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Optimizing The Cut And Count Method In Phenomenological Studies
An iterative ranking-based optimization of cut-and-count using MadAnalysis5 enhances signal-background separation and discovery reach for singly charged Higgs in the Two Higgs Doublet Model.