Constraints on Dark Energy Models from Galaxy Clusters with Multiple Arcs

Details Constraints on Dark Energy Models from Galaxy Clusters with Multiple Arcs Constraints on Dark Energy Models from Galaxy Clusters with Multiple Arcs

2004-09-02

arxiv.org/abs/astro-ph/0409030v1

Mon.Not.Roy.Astron.Soc. 362 (2005) 1301-1310

Astronomy and Astrophysics

Astrophysics

10 pages, 8 figures, submitted to MNRAS

Scientific paper

10.1111/j.1365-2966.2005.09402.x

We make an exploratory study of how well dark energy models can be constrained using lensed arcs at different redshifts behind cluster lenses. Arcs trace the critical curves of clusters, and the growth of critical curves with source redshift is sensitive to the dark-energy equation of state. Using analytical models and numerically simulated clusters, we explore the key factors involved in using cluster arcs as a probe of dark energy. We quantify the sensitivity to lens mass, concentration and ellipticity with analytical models that include the effects of dark energy on halo structure. We show with simple examples how degeneracies between mass models and cosmography may be broken using arcs at multiple redshifts or additional constraints on the lens density profile. However we conclude that the requirements on the data are so stringent that it is very unlikely that robust constraints can be obtained from individual clusters. We argue that surveys of clusters, analyzed in conjunction with numerical simulations, are a more promising prospect for arc-cosmography. We use such numerically simulated clusters to estimate how large a sample of clusters/arcs could provide interesting constraints on dark energy models. We focus on the scatter produced by differences in the mass distribution of individual clusters. We find from our sample of simulated clusters that at least 1000 pairs of arcs are needed to obtain constraints if the mass distribution of individual clusters is taken to be undetermined. We discuss several unsolved problems that need study to fully develop this method for precision studies with future surveys.

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