The Gini Coefficient as a Tool for Image Family Identification in Strong Lensing Systems with Multiple Images
Journal Article
·
· The Astrophysical Journal. Letters (Online)
- Univ. of Chicago, IL (United States)
- Univ. of Chicago, IL (United States); Argonne National Lab. (ANL), Lemont, IL (United States)
- Univ. of Michigan, Ann Arbor, MI (United States)
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.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- National Science Foundation (NSF); USDOE Office of Science; Univ. of Chicago, Kavli Institute for Cosmological Physics
- Grant/Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1248958
- Alternate ID(s):
- OSTI ID: 22518637
- Journal Information:
- The Astrophysical Journal. Letters (Online), Journal Name: The Astrophysical Journal. Letters (Online) Journal Issue: 2 Vol. 816; ISSN 2041-8213
- Publisher:
- Institute of Physics (IOP)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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