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Bayesian approach and Naturalness in MSSM analyses for the LHC · Around

2008

Bayesian approach and Naturalness in MSSM analyses for the LHC

Cabrera, M. E., Casas, J. A., de Austri, R. Ruiz

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The start of LHC has motivated an effort to determine the relative probability of the different regions of the MSSM parameter space, taking into account the present, theoretical and experimental, wisdom about the model.

Since the present experimental data are not powerful enough to select a small region of the MSSM parameter space, the choice of a judicious prior probability for the parameters becomes most relevant.
Previous studies have proposed theoretical priors that incorporate some (conventional) measure of the fine-tuning, to penalize unnatural possibilities.
However, we show that such penalization arises from the Bayesian analysis itself (with no ad hoc assumptions), upon the marginalization of the mu-parameter.

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B. C. Allanach and C. G. Lester, Phys. Rev. D 73

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R. Trotta, F. Feroz, M. P. Hobson, L. Roszkowski and R. Ruiz de Austri, arXiv:0809.3792 [hep-ph]

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