Abstract

The major task for present and future dark energy surveys is to determine whether dark energy is evolving in time. Using the latest cosmological datasets (SN, CMB and LSS ), we have performed a Bayesian analysis to extract the general form of the dark energy equation-of-state parameter, employing an optimal nodal reconstruction where w(z) is interpolated linearly between a set of nodes with varying w_z-amplitudes and redshifts. Our method has the advantage that the number and location of nodes are directly chosen by the Bayesian evidence. We find our results to be generally consistent with the cosmological constant scenario, though with weak evidence for some temporal evolution as well. Besides the cosmological constant, the preferred w(z) has w 1 the accuracy of current data is not enough to place effective constraints on different parameterisations. We also attempted to fit an optimal degree of structure for the primordial power spectrum of curvature perturbations using the Bayesian model selection as our discriminating criterion. The preferred model is provided by the Lasenby and Doran model followed by a modified power-law version. We found that the power-law parameterisation, including either cases, spectral index n_s and running of the index n_{run}, are both significantly disfavoured.