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Bayesian Study and Naturalness in MSSM Forecast for the LHC

2010/05/14 by María Eugenia Cabrera, Maria Eugenia Cabrera, Cabrera, Maria Eugenia · 1 citation
Physics and Astronomy · #Dark Matter and Cosmic Phenomena #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #High-Energy Particle Collisions Research #Particle physics theoretical and experimental studies #hep-ph

paper · pdf · doi:10.48550/arxiv.1005.2525

Presented at Recontres de Moriond EW 2010, 6-13 March 2010

arxiv created 2010/05/14 · openalex publication_date 2010/05/14 · arxiv updated 2010/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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

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