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Bayesian Study and Naturalness in MSSM Forecast for the LHC

We perform a forecast of the CMSSM for the LHC based in an improved Bayesian analysis taking into account the present theoretical and experimental wisdom about the model. In this way we obtain a map of the preferred regions of the CMSSM parameter space and show that fine-tuning penalization arises from the Bayesian analysis itself when the experimental value of Mz is considered. The results are remarkable stable when using different priors

preprint2010arXivOpen access
Maria Eugenia Cabrera
hep-ph
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Maria Eugenia Cabrera

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