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Author (up) Cabrera, M.E.; Casas, J.A.; Ruiz de Austri, R.
Title MSSM forecast for the LHC Type Journal Article
Year 2010 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.
Volume 05 Issue 5 Pages 043 - 48pp
Keywords Beyond Standard Model; Supersymmetric Effective Theories
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-mu possibilities.
Address [Eugenia Cabrera, Maria; Alberto Casas, J.] UAM, IFT UAM CSIC, Inst Fis Teor, Madrid 28049, Spain, Email: maria.cabrera@uam.es
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1126-6708 ISBN Medium
Area Expedition Conference
Notes ISI:000278251300005 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ elepoucu @ Serial 435
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