We develop an efficient, non-parametric Bayesian method for reconstructing the time evolution of the dark energy equation of state w(z) from observational data. Of particular importance is the choice of prior, which must be chosen carefully to minimise variance and bias in the reconstruction. Using a principal component analysis, we show how a correlated prior can be used to create a smooth reconstruction and also avoid bias in the mean behaviour of w(z). We test our method using Wiener reconstructions based on Fisher matrix projections, and also against more realistic MCMC analyses of simulated data sets for Planck and a future space-based dark energy mission. While the accuracy of our reconstruction depends on the smoothness of the assumed w(z), the relative error for typical dark energy models is <10% out to redshift z=1.5.
We present a global measurement of the integrated Sachs-Wolfe (ISW) effect obtained by cross-correlating all relevant large scale galaxy data sets with the cosmic microwave background radiation map provided by the Wilkinson Microwave Anisotropy Probe. With these measurements, the overall ISW signal is detected at the ~ 4.5 sigma level. We also examine the cosmological implications of these measurements, particularly the dark energy equation of state w, its sound speed, and the overall curvature of the Universe. The flat LCDM model is a good fit to the data and, assuming this model, we find that the ISW data constrain Omega_m = 0.20 +0.19 -0.11 at the 95% confidence level. When we combine our ISW results with the latest baryon oscillation and supernovae measurements, we find that the result is still consistent with a flat LCDM model with w = -1 out to redshifts z > 1.
