Implications for the Constrained MSSM from a new prediction for b to s gamma

TL;DR

This paper re-evaluates the Constrained MSSM considering recent updates in the Standard Model prediction for B to X_s gamma, highlighting the favored parameter regions and implications for dark matter and collider searches.

Contribution

It provides a Bayesian analysis of the Constrained MSSM with updated constraints, emphasizing the focus point region and the impact of recent B to X_s gamma measurements.

Findings

Preference for >0 case with focus point region

Improved prospects for neutralino dark matter detection

Challenges for superpartner searches at the LHC

Abstract

We re-examine the properties of the Constrained MSSM in light of updated constraints, paying particular attention to the impact of the recent substantial shift in the Standard Model prediction for BR(B to X_s gamma). With the help of a Markov Chain Monte Carlo scanning technique, we vary all relevant parameters simultaneously and derive Bayesian posterior probability maps. We find that the case of \mu>0 remains favored, and that for \mu<0 it is considerably more difficult to find a good global fit to current constraints. In both cases we find a strong preference for a focus point region. This leads to improved prospects for detecting neutralino dark matter in direct searches, while superpartner searches at the LHC become more problematic, especially when \mu<0. In contrast, prospects for exploring the whole mass range of the lightest Higgs boson at the Tevatron and the LHC remain very good, which should, along with dark matter searches, allow one to gain access to the otherwise experimentally challenging focus point region. An alternative measure of the mean quality-of-fit which we also employ implies that present data are not yet constraining enough to draw more definite conclusions. We also comment on the dependence of our results on the choice of priors and on some other assumptions.