Interpreting LHC SUSY searches in the phenomenological MSSM

TL;DR

This paper interprets early LHC SUSY search results within the broad 19-parameter phenomenological MSSM using Bayesian analysis, providing more general constraints than specific models like the CMSSM.

Contribution

It offers a comprehensive Bayesian analysis of LHC data in the pMSSM, capturing a wide range of SUSY phenomenology beyond traditional constrained models.

Findings

Posterior probability densities of parameters and masses derived.

More generic constraints on MSSM from LHC data.

Analysis surpasses specific models like CMSSM in generality.

Abstract

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 MSSM that captures most of its phenomenological features. It encompasses, and goes beyond, a broad range of more constrained SUSY models. Performing a global Bayesian analysis, we obtain posterior probability densities of parameters, masses and derived observables. In contrast to constraints derived for particular SUSY breaking schemes, such as the CMSSM, our results provide more generic conclusions on how the current data constrain the MSSM.