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Once supersymmetry is found at the LHC, the question arises what are the fundamental parameters of the Lagrangian. The answer to this question should thereby not be biased by assumptions on high-scale models. SFitter is a tool designed for this task. Taking LHC (and possibly ILC) data as input it scans the TeV-scale MSSM parameter space using its new weighted Markov chain technique. Using this scan it determines a list of best-fitting parameter points. Additionally a log-likelihood map is calculated, which can be reduced to lower-dimensional Frequentists profile likelihoods or Bayesian probability maps.
SFITTER is a new analysis tool to determine supersymmetric model parameters from collider measurements. Using the set of supersymmetric mass measurements at the LC and at the LHC we show how both colliders probe different sectors of the MSSM Lagrangi
ATLAS and CMS collaborations have reported the results on the Higgs search analyzing $sim 36$ fb$^{-1}$ data from Run-II of LHC at 13 TeV. In this work, we study the Higgs sector of the phenomenological Minimal Supersymmetric Standard Model, in light
In this analysis we explore the phenomenological constraints of models with non-holomorphic soft SUSY breaking terms in a beyond the MSSM scenario having identical particle content. The model referred as NHSSM shows various promising features like th
We describe a likelihood analysis using MasterCode of variants of the MSSM in which the soft supersymmetry-breaking parameters are assumed to have universal values at some scale $M_{in}$ below the supersymmetric grand unification scale $M_{GUT}$, as
We interpret within the phenomenological MSSM (pMSSM) the results of SUSY searches published by the CMS collaboration based on the first ~1 fb^-1 of data taken during the 2011 LHC run at 7 TeV. The pMSSM is a 19-dimensional parametrization of the MSS