2011MNRAS.411.1628D

We explore the use of strong lensing by galaxy clusters to constrain the dark energy equation of state and its possible time variation. The cores of massive clusters often contain several multiply imaged systems of background galaxies at different redshifts. The locations of lensed images can be used to constrain cosmological parameters due to their dependence on the ratio of angular diameter distances. We employ Monte Carlo simulations of cluster lenses, including the contribution from substructures, to assess the feasibility of this potentially powerful technique. At the present, parametric lens models use well-motivated scaling relations between mass and light to incorporate cluster member galaxies and do not explicitly model line-of-sight structure. Here, we quantify modelling errors due to scatter in the cluster-galaxy scaling relations and unmodelled line-of-sight haloes. These errors are of the order of a few arcseconds on average for clusters located at typical redshifts (z∼ 0.2-0.3). Using Bayesian Markov chain Monte Carlo techniques, we show that the inclusion of these modelling errors is critical to deriving unbiased constraints on dark energy. However, when the uncertainties are properly quantified, we show that constraints competitive with other methods may be obtained by combining results from a sample of just 10 simulated clusters with 20 families each. Cosmography with a set of well-studied cluster lenses may provide a powerful complementary probe of the dark energy equation of state. Our simulations provide a convenient method of quantifying modelling errors and assessing future strong lensing survey strategies.