Full Lensing Analysis of Abell 1703: Comparison of Independent Lens-Modelling Techniques

TL;DR

This study compares parametric and non-parametric strong lensing techniques on Abell 1703, integrating weak lensing data to derive a consistent mass profile, revealing the cluster's high concentration compared to standard cosmological predictions.

Contribution

It demonstrates the consistency of different lensing methods and combines strong and weak lensing data to accurately determine the cluster's mass profile and concentration.

Findings

Both lensing methods agree on the large-scale dark matter distribution.

The combined profile fits an NFW model with high concentration.

Abell 1703 has a higher concentration than predicted by standard models.

Abstract

The inner mass-profile of the relaxed cluster Abell 1703 is analysed by two very different strong-lensing techniques applied to deep ACS and WFC3 imaging. Our parametric method has the accuracy required to reproduce the many sets of multiple images, based on the assumption that mass approximately traces light. We test this assumption with a fully non-parametric, adaptive grid method, with no knowledge of the galaxy distribution. Differences between the methods are seen on fine scales due to member galaxies which must be included in models designed to search for lensed images, but on the larger scale the general distribution of dark matter is in good agreement, with very similar radial mass profiles. We add undiluted weak-lensing measurements from deep multi-colour Subaru imaging to obtain a fully model-independent mass profile out to the virial radius and beyond. Consistency is found in the region of overlap between the weak and strong lensing, and the full mass profile is well-described by an NFW model of a concentration parameter, $c_{\rm vir}\simeq 7.15\pm0.5$ (and $M_{vir}\simeq 1.22\pm0.15 \times 10^{15}M_{\odot}/h$). Abell 1703 lies above the standard $c$--$M$ relation predicted for the standard $\Lambda$CDM model, similar to other massive relaxed clusters with accurately determined lensing-based profiles.