2023/05/18 by Baradhwaj Coleppa, Gokul B. Krishna, Coleppa, Baradhwaj +5
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #Dark Matter and Cosmic Phenomena #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #Particle physics theoretical and experimental studies
paper · pdf · doi:10.48550/arxiv.2305.10915
openalex publication_date 2023/05/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We introduce an optimization technique to discriminate signal and background in any phenomeno- logical study based on the cut and count-based method. The core ideas behind this technique are the introduction of a ranking scheme that can quantitatively assess the relative importance of var- ious observables involved in a new physics process, and a more methodical way of choosing what cuts to impose. The technique is an iterative process that works with the help of the MadAnalysis5 interface. Working in the context of a BSM (Beyond Standard Model) scenario where we carry out a signal search of singly charged Higgs in the context of the Two Higgs Doublet Model (2HDM), we demonstrate how automating the cut and count process in this specific way results in an enhanced discovery potential compared with the more traditional way of imposing cuts.