Dark energy constraints and correlations with systematics from CFHTLS weak lensing, SNLS supernovae Ia and WMAP5

Details Dark energy constraints and correlations with systematics from CFHTLS weak lensing, SNLS supernovae Ia and WMAP5 Dark energy constraints and correlations with systematics from CFHTLS weak lensing, SNLS supernovae Ia and WMAP5

2008-10-28

arxiv.org/abs/0810.5129v2

Astronomy and Astrophysics

Astrophysics

14 pages, 10 figures. Revised version, matches the one to be published in A&A. Modifications have been made corresponding to t

Scientific paper

10.1051/0004-6361/200811247

We combine measurements of weak gravitational lensing from the CFHTLS-Wide survey, supernovae Ia from CFHT SNLS and CMB anisotropies from WMAP5 to obtain joint constraints on cosmological parameters, in particular, the dark energy equation of state parameter w. We assess the influence of systematics in the data on the results and look for possible correlations with cosmological parameters. We implement an MCMC algorithm to sample the parameter space of a flat CDM model with a dark-energy component of constant w. Systematics in the data are parametrised and included in the analysis. We determine the influence of photometric calibration of SNIa data on cosmological results by calculating the response of the distance modulus to photometric zero-point variations. The weak lensing data set is tested for anomalous field-to-field variations and a systematic shape measurement bias for high-z galaxies. Ignoring photometric uncertainties for SNLS biases cosmological parameters by at most 20% of the statistical errors, using supernovae only; the parameter uncertainties are underestimated by 10%. The weak lensing field-to-field variance pointings is 5%-15% higher than that predicted from N-body simulations. We find no bias of the lensing signal at high redshift, within the framework of a simple model. Assuming a systematic underestimation of the lensing signal at high redshift, the normalisation sigma_8 increases by up to 8%. Combining all three probes we obtain -0.10<1+w<0.06 at 68% confidence (-0.18<1+w<0.12 at 95%), including systematic errors. Systematics in the data increase the error bars by up to 35%; the best-fit values change by less than 0.15sigma. [Abridged]

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