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Título: | Frequentist analysis of the parameter space of minimal supergravity |
Autor: | Buchmueller, O.; Heinemeyer, Sven CSIC ORCID ; Weiglein, G. | Fecha de publicación: | 2011 | Editor: | Springer Nature | Citación: | European Physical Journal C 71(3): 1583 (2011) | Resumen: | We make a frequentist analysis of the parameter space of minimal supergravity (mSUGRA), in which, as well as the gaugino and scalar soft supersymmetry-breaking parameters being universal, there is a specific relation between the trilinear, bilinear and scalar supersymmetry-breaking parameters, A 0=B 0+m 0, and the gravitino mass is fixed by m 3/2=m 0. We also consider a more general model, in which the gravitino mass constraint is relaxed (the VCMSSM). We combine in the global likelihood function the experimental constraints from low-energy electroweak precision data, the anomalous magnetic moment of the muon, the lightest Higgs boson mass M h , B physics and the astrophysical cold dark matter density, assuming that the lightest supersymmetric particle (LSP) is a neutralino. In the VCMSSM, we find a preference for values of m 1/2 and m 0 similar to those found previously in frequentist analyses of the constrained MSSM (CMSSM) and a model with common non-universal Higgs masses (NUHM1). On the other hand, in mSUGRA we find two preferred regions: one with larger values of both m 1/2 and m 0 than in the VCMSSM, and one with large m 0 but small m 1/2. We compare the probabilities of the frequentist fits in mSUGRA, the VCMSSM, the CMSSM and the NUHM1: the probability that mSUGRA is consistent with the present data is significantly less than in the other models. We also discuss the mSUGRA and VCMSSM predictions for sparticle masses and other observables, identifying potential signatures at the LHC and elsewhere. | URI: | http://hdl.handle.net/10261/51935 | DOI: | 10.1140/epjc/s10052-011-1583-8 | Identificadores: | doi: 10.1140/epjc/s10052-011-1583-8 issn: 1434-6044 e-issn: 1434-6052 |
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Frequentist analysis.pdf | 2,2 MB | Adobe PDF | Visualizar/Abrir |
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