The CMSSM and NUHM1 in Light of 7 TeV LHC, B_s to mu+mu- and XENON100 Data

TL;DR

This paper performs a comprehensive statistical analysis of the CMSSM and NUHM1 supersymmetric models using recent LHC, B_s to mu+mu-, and XENON100 data, constraining their parameter spaces and assessing their viability.

Contribution

It introduces a large-scale Markov Chain Monte Carlo analysis incorporating latest experimental constraints to evaluate the parameter spaces of CMSSM and NUHM1 models.

Findings

ATLAS 7 TeV data has limited impact on (m_0, m_1/2) regions.

B_s to mu+mu- data significantly constrains tan beta and M_A.

XENON100 data excludes the focus-point region in CMSSM.

Abstract

We make a frequentist analysis of the parameter space of the CMSSM and NUHM1, using a Markov Chain Monte Carlo (MCMC) with 95 (221) million points to sample the CMSSM (NUHM1) parameter spaces. Our analysis includes the ATLAS search for supersymmetric jets + MET signals using ~ 5/fb of LHC data at 7 TeV, which we apply using PYTHIA and a Delphes implementation that we validate in the relevant parameter regions of the CMSSM and NUHM1. Our analysis also includes the constraint imposed by searches for B_s to mu+mu- by LHCb, CMS, ATLAS and CDF, and the limit on spin-independent dark matter scattering from 225 live days of XENON100 data. We assume M_h ~ 125 GeV, and use a full set of electroweak precision and other flavour-physics observables, as well as the cold dark matter density constraint. The ATLAS 5/fb constraint has relatively limited effects on the 68 and 95% CL regions in the (m_0, m_1/2) planes of the CMSSM and NUHM1. The new B_s to mu+mu- constraint has greater impacts on these CL regions, and also impacts significantly the 68 and 95% CL regions in the (M_A, tan beta) planes of both models, reducing the best-fit values of tan beta. The recent XENON100 data eliminate the focus-point region in the CMSSM and affect the 68 and 95% CL regions in the NUHM1. In combination, these new constraints reduce the best-fit values of m_0, m_1/2 in the CMSSM, and increase the global chi^2 from 31.0 to 32.8, reducing the p-value from 12% to 8.5%. In the case of the NUHM1, they have little effect on the best-fit values of m_0, m_1/2, but increase the global chi^2 from 28.9 to 31.3, thereby reducing the p-value from 15% to 9.1%.