Abstract: We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of similar to 10(4) with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.

Abstract: We present a Bayesian analysis of the NUGHM, a supersymmetric scenario with non-universal gaugino masses and Higgs masses, including all the relevant experimental observables and dark matter constraints. The main merit of the NUGHM is that it essentially includes all the possibilities for dark matter (DM) candidates within the MSSM, since the neutralino and chargino spectrum -and composition- are as free as they can be in the general MSSM. We identify the most probable regions in the NUHGM parameter space, and study the associated phenomenology at the LHC and the prospects for DM direct detection. Requiring that the neutralino makes all of the DM in the Universe, we identify two preferred regions around m(chi 10) = 1 TeV, 3 TeV, which correspond to the (almost) pure Higgsino and wino case. There exist other marginal regions (e.g. Higgs-funnel), but with much less statistical weight. The prospects for detection at the LHC in this case are quite pessimistic, but future direct detection experiments like LUX and XENON1T, will be able to probe this scenario. In contrast, when allowing other DM components, the prospects for detection at the LHC become more encouraging – the most promising signals being, beside the production of gluinos and squarks, the production of the heavier chargino and neutralino states, which lead to WZ and same-sign WW final states – and direct detection remains a complementary, and even more powerful, way to probe the scenario.

Abstract: We analyze the implications for the status and prospects of supersymmetry of the Higgs discovery and the last XENON data. We focus mainly, but not only, on the CMSSM and NUHM models. Using a Bayesian approach we determine the distribution of probability in the parameter space of these scenarios. This shows that, most probably, they are now beyond the LHC reach. This negative chances increase further (at more than 95% c.l.) if one includes dark matter constraints in the analysis, in particular the last XENON100 data. However, the models would be probed completely by XENON1T. The mass of the LSP neutralino gets essentially fixed around 1TeV. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises automatically from the careful Bayesian analysis itself, and allows to scan the whole parameter space. In this way, we can explain and resolve the apparent discrepancies between the previous results in the literature. Although SUSY has become hard to detect at LHC, this does not necessarily mean that is very fine-tuned. We use Bayesian techniques to show the experimental Higgs mass is at similar to 2 sigma off the CMSSM or NUHM expectation. This is substantial but not dramatic. Although the CMSSM or the NUHM are unlikely to show up at the LHC, they are still interesting and plausible models after the Higgs observation; and, if they are true, the chances of discovering them in future dark matter experiments are quite high.