MSSM forecast for the LHC

Abstract

Abstract:We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of M Z is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on e + e − data) is considered, the preferred region (for µ > 0) is well inside the LHC scope. We also perform a Bayesian comparison of the positive-and negative-µ possibilities.

What is a natural SUSY scenario?

“…space is multiplied by ∆ −1 µ , which is consistent with the above probabilistic interpretation of ∆ [45,89,91,92]. Actually, the equivalence is exact if one assumes that the prior in the parameters is factorizable, i.e.…”

Global fits of the minimal universal extra dimensions scenario

“…[56] for an explicit expression for J), µ Z is the value of µ that reproduces the experimental value of M Z for the given values of {s, m 0 , m 1/2 , A 0 , B} and P (s, m, M, A, B, µ) is the prior in the initial parameters (For a detailed discussion on the chosen priors see Ref. [57]). One of the main consequences of this approach is that the results exhibit a remarkable robustness under changes of the priors (see Ref.…”

“…One of the main consequences of this approach is that the results exhibit a remarkable robustness under changes of the priors (see Ref. [57]), showing an absence of dependences on the initial chosen ranges for the CMSSM parameters. Moreover the results are compatible with likelihood based analyses [58].…”

“…[59], where a similar analysis is performed). The experimental data used in constraining the latter are given in Table 2 of [57]. Regions in light green (dark green) are within the reach of the LHC with 7 TeV and 1 fb −1 (with 14 TeV and 100 fb −1 , respectively) for both models, while red regions are outside the reach of the LHC.…”

Indirect and direct detection prospect for TeV dark matter in the nine parameter MSSM

“…Therefore, this measurement already significantly constrains the parameter space of supersymmetric models. Reference [8] studied the implications of the Higgs mass measurement for the minimal supersymmetric standard model (MSSM) with five parameters (the constrained MSSM), and found that the posterior probabilities for these parameters are narrowly distributed. Reference [9] further extended the model to include the nonuniversality in gaugino and Higgs masses, and found qualitatively similar results.…”