Implications for the Constrained MSSM from a new prediction forb→sγ

Abstract

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 → X s γ). 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 µ > 0 remains favored, and that for µ < 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 µ < 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.

Publisher’s Note: Global fits of the nonuniversal Higgs model [Phys. Rev. D83, 015014 (2011)]

“…The likelihood function is not strong enough to completely override this preference, and hence the posterior remains influenced by the prior. This statistical effect has already been noticed in the case of the CMSSM [37,26,19]. The profile likelihood for BR(B → X s γ) and (g − 2) µ instead follows closely the values of the likelihood function.…”

“…As in previous works [14,17,26], we adopt a Metropolis-Hastings MCMC algorithm to sample the parameter space. We have also cross-checked our results by employing the more recently implemented MultiNest algorithm [27,19] and the findings are compatible (up to numerical noise).…”

SUSY predictions and SUSY tools at the LHC

“…The fact that the frequentist interpretation differs from the Bayesian one can be seen as a signal that more data is required for the fit; indeed we should not be surprised since a complex model with eight free parameters has been fit with some fairly indirect data. Similar fits to the Bayesian ones above were performed using the Metropolis MCMC algorithm, resulting in quite similar posterior probability densities for the particle physics properties, despite some differences in the indirect constraints used [64]. In addition, ref.…”

“…In addition, ref. [64] constrains dark matter detection cross-sections. We show the posterior probability distribution function of the spin-independent direct dark matter detection cross-section in Fig.…”

First limits on WIMP dark matter from the XENON10 experiment

“…The light gray area indicates the DAMA (NaI) annual modulation, if interpreted as DM signal [16]. The light and dark red areas are expectations for parameters in the constrained minimal supersymmetric models [2,17]. cuts, including the energy window of 4.5 -26.9 keV nuclear recoil equivalent energy and a fiducial volume corresponding to 5.4 kg detector mass.…”