Cosmography with cluster strong lenses: the influence of substructure and line-of-sight halos

TL;DR

This paper investigates how strong lensing by galaxy clusters can be used to constrain dark energy, emphasizing the importance of modeling errors from substructure and line-of-sight halos, and demonstrates that competitive constraints are achievable with a small sample of clusters.

Contribution

It introduces a Monte-Carlo simulation approach to quantify modeling errors in cluster lensing and shows that incorporating these errors enables unbiased dark energy constraints from limited data.

Findings

Modeling errors are about a few arcseconds for typical clusters.

Properly accounting for errors yields competitive dark energy constraints.

A sample of 10 clusters can provide meaningful cosmological insights.

Abstract

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 modeling errors due to scatter in the cluster galaxy scaling relations and un-modeled line-of-sight halos. 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 modeling 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 modeling errors and assessing future strong lensing survey strategies.