4.4 Article

Bayesian selection of sign mu within mSUGRA in global fits including WMAP5 results

Journal

JOURNAL OF HIGH ENERGY PHYSICS
Volume -, Issue 10, Pages -

Publisher

SPRINGER
DOI: 10.1088/1126-6708/2008/10/064

Keywords

Supersymmetric Standard Model; Supersymmetry Phenomenology

Funding

  1. STFC
  2. EU FP6 Marie Curie Research AMP
  3. Training Network [MRTN-CT-2006-035863]
  4. Cambridge Commonwealth Trust
  5. Isaac Newton Trust
  6. Pakistan Higher Education Commission Fellowships
  7. Gates Cambridge Trust
  8. Royal Astronomical Society, St Anne's College, Oxford
  9. European Network of Theoretical Astroparticle Physics ENTApP ILIAS/N6 [RII3-CT-2004-506222]
  10. Science and Technology Facilities Council [ST/G000581/1] Funding Source: researchfish

Ask authors/readers for more resources

We study the properties of the constrained minimal supersymmetric standard model (mSUGRA) by performing fits to updated indirect data, including the relic density of dark matter inferred from WMAP5. In order to find the extent to which mu < 0 is dis-favoured compared to mu > 0, we compare the Bayesian evidence values for these models, which we obtain straightforwardly and with good precision from the recently developed multi-modal nested sampling ('MultiNest') technique. We find weak to moderate evidence for the mu > 0 branch of mSUGRA over mu < 0 and estimate the ratio of probabilities to be P( mu > 0)/P( mu < 0) = 6-61 depending on the prior measure and range used. There is thus positive ( but not overwhelming) evidence that mu > 0 in mSUGRA. The MULTINEST technique also delivers probability distributions of parameters and other relevant quantities such as superpartner masses. We explore the dependence of our results on the choice of the prior measure used. We also use the Bayesian evidence to quantify the consistency between the mSUGRA parameter inferences coming from the constraints that have the largest effects: (g-2)(mu), BR(b -> s gamma) and cold dark matter (DM) relic density Omega(DM)h(2).

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available