Model-independent and model-based local lensing properties of CL0024+1654 from multiply imaged galaxies

Abstract

Context. Local gravitational lensing properties, like convergence and shear, determined at the positions of multiply-imaged background objects, yield valuable information on the smaller-scale lensing matter distribution in the central part of galaxy clusters. Highly distorted multiple images with resolved brightness features like the ones observed in CL0024 allow to study these local lensing properties to tighten the constraints on the properties of dark matter on sub-cluster scale. Aims. We investigate to which precision local magnification ratios, J, ratios of convergences, f , and reduced shears, g = (g1, g2), can be determined model-independently for the five resolved multiple images of the source at zs = 1.675 in CL0024. We also determine if a comparison to the respective results obtained by the parametric modelling program Lenstool and by the non-parametric modelling program Grale can detect biases in the lens models. For these model-based approaches we additionally analyse the influence of the number and location of the constraints from multiple images on the local lens properties determined at the positions of the five multiple images of the source at zs = 1.675. Methods. Our model-independent approach uses a linear mapping between the five resolved multiple images to determine the magnifi- cation ratios, ratios of convergences, and reduced shears at their positions.With constraints from up to six multiple image systems, we generate Lenstool and Grale models using the same image positions, cosmological parameters, and number of generated convergence and shear maps to determine the local values of J, f , and g at the same positions across all methods. Results. All approaches show high agreement on the local values of J, f , and g. We find that Lenstool obtains the tightest confidence bounds even for convergences around one using constraints from six multiple image systems, while the best Grale model is generated only using constraints from all multiple images with resolved brightness features and adding limited small-scale mass corrections. Yet, confidence bounds as large as the values themselves can occur for convergences close to one in all approaches. Conclusions. Our results are in agreement with previous findings, supporting the light-traces-mass assumption and the merger hypothesis for CL0024. Comparing the three different approaches allows to detect modelling biases. Given that the lens properties remain approximately constant over the extension of the image areas covered by the resolvable brightness features, the model-independent approach determines the local lens properties to a comparable precision but within less than a second.