The Gini Coefficient as a Tool for Image Family Idenitification in Strong Lensing Systems with Multiple Images

TL;DR

This paper explores the use of the Gini coefficient as a morphological metric to improve the identification of multiple image families in strong lensing systems, enhancing accuracy without extra observational data.

Contribution

It demonstrates that the Gini coefficient can serve as an effective diagnostic tool for image family identification, complementing color information and reducing degeneracies.

Findings

Gini coefficient remains well-preserved in strong lensing images.

Using Gini coefficients alongside color improves image family identification.

The method reduces reliance on additional observational data.

Abstract

The sample of cosmological strong lensing systems has been steadily growing in recent years and with the advent of the next generation of space-based survey telescopes, the sample will reach into the thousands. The accuracy of strong lens models relies on robust identification of multiple image families of lensed galaxies. For the most massive lenses, often more than one background galaxy is magnified and multiply-imaged, and even in the cases of only a single lensed source, identification of counter images is not always robust. Recently, we have shown that the Gini coefficient in space-telescope-quality imaging is a measurement of galaxy morphology that is relatively well-preserved by strong gravitational lensing. Here, we investigate its usefulness as a diagnostic for the purposes of image family identification and show that it can remove some of the degeneracies encountered when using color as the sole diagnostic, and can do so without the need for additional observations since whenever a color is available, two Gini coefficients are as well.