Speaker
Description
Beyond the Standard Model (BSM) searches show no statistically significant sign of new physics to date. However, several analyses reported small excesses, higher than 2σ SD beyond the SM expectation. In this work, clustering algorithms are used to extract additional insights from existing searches and to motivate a next round of BSM analyses. The flexible framework of the phenomenological Minimal Supersymmetric Standard Model (pMSSM) is used for a large-scale reinterpretation of new physics models using existing analyses. Models consistent with the observed excesses are explored using clustering methods. In this work, clustering algorithms are benchmarked for this high-dimensional problem. Optimal algorithms are deployed to perform a large-scale reinterpretation of new physics searches to help inform the direction of future searches at the HL-LHC.