A Bayesian analysis of the primordial power spectrum

We present a Bayesian analysis of large-scale structure (LSS) and cosmic microwave background data to constrain the form of the primordial power spectrum. We have extended the usual presumption of a scale-invariant spectrum to include (i) a running spectral index; (ii) a broken spectrum arising perhaps from an interruption of the potential driving inflation; (iii) a large-scale cut-off in power as the first year Wilkinson Microwave Anisotropy Probe (WMAP) results appear to indicate; (iv) a reconstruction of the spectrum in eight bins in wavenumber; and (v) a spectrum resulting from a cosmological model proposed by Lasenby & Doran, which naturally exhibits an exponential drop in power on very large scales. The result of our complete Bayesian analysis includes not only the posterior probability distribution from which parameter estimates are inferred but also the Bayesian evidence. This evidence value is greater for a model with fewer parameters unless a more complicated model provides a significantly better fit to the data, thus allowing a powerful method of model selection. We find that those models exhibiting any form of cut-off in power on large scales consistently produce higher evidences than either the Harrison-Zel'dovich or single spectral index spectra. In particular, within the best-fitting concordance cosmology, we find the Lasenby & Doran spectrum to show significantly larger evidence as compared to the other models.