Model selection forecasts for the spectral index from the Planck satellite

The recent WMAP3 results have placed measurements of the spectral index n_S in an interesting position. While parameter estimation techniques indicate that the Harrison-Zel'dovich spectrum n_S=1 is strongly excluded (in the absence of tensor perturbations), Bayesian model selection techniques reveal that the case against n_S=1 is not yet conclusive. In this paper, we forecast the ability of the Planck satellite mission to use Bayesian model selection to convincingly exclude (or favour) the Harrison-Zel'dovich model.Comment: 4 pages RevTeX with one figure included. Updated to match PRD accepted version. Improved likelihood function implementation; no qualitative change to results but some tiny numerical shift

Bayesian analysis of Friedmannless cosmologies

Assuming only a homogeneous and isotropic universe and using both the 'Gold' Supernova Type Ia sample of Riess et al. and the results from the Supernova Legacy Survey, we calculate the Bayesian evidence of a range of different parameterizations of the deceleration parameter. We consider both spatially flat and curved models. Our results show that although there is strong evidence in the data for an accelerating universe, there is little evidence that the deceleration parameter varies with redshift.Comment: 7 pages, 3 figure

A Bayesian model selection analysis of WMAP3

We present a Bayesian model selection analysis of WMAP3 data using our code CosmoNest. We focus on the density perturbation spectral index $n_S$ and the tensor-to-scalar ratio $r$, which define the plane of slow-roll inflationary models. We find that while the Bayesian evidence supports the conclusion that $n_S \neq 1$, the data are not yet powerful enough to do so at a strong or decisive level. If tensors are assumed absent, the current odds are approximately 8 to 1 in favour of $n_S \neq 1$ under our assumptions, when WMAP3 data is used together with external data sets. WMAP3 data on its own is unable to distinguish between the two models. Further, inclusion of $r$ as a parameter weakens the conclusion against the Harrison-Zel'dovich case (n_S = 1, r=0), albeit in a prior-dependent way. In appendices we describe the CosmoNest code in detail, noting its ability to supply posterior samples as well as to accurately compute the Bayesian evidence. We make a first public release of CosmoNest, now available at http://www.cosmonest.org.Comment: 7 pages RevTex with 4 figures included. Updated to match PRD accepted version. Main results unchanged. CosmoNest code now version 1.0 and includes calculation of the Information. Code available at http://www.cosmonest.or