2008/07/09 by Thorsten Lisker
Physics and Astronomy · #Astronomy and Astrophysical Research #Galaxies: Formation, Evolution, Phenomena #Gamma-ray bursts and supernovae #astro-ph
paper · pdf · doi:10.1086/591795
Accepted by ApJS. 7 pages, incl. 4 figures
arxiv created 2008/07/09 · openalex publication_date 2008/11/25 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
The Gini coefficient, a non-parametric measure of galaxy morphology, has recently taken up an important role in the automated identification of galaxy mergers. I present a critical assessment of its stability, based on a comparison of HST/ACS imaging data from the GOODS and UDF surveys. Below a certain signal-to-noise level, the Gini coefficient depends strongly on the signal-to-noise ratio, and thus becomes useless for distinguishing different galaxy morphologies. Moreover, at all signal-to-noise levels the Gini coefficient shows a strong dependence on the choice of aperture within which it is measured. Consequently, quantitative selection criteria involving the Gini coefficient, such as a selection of merger candidates, cannot always be straightforwardly applied to different datasets. I discuss whether these effects could have affected previous studies that were based on the Gini coefficient, and establish signal-to-noise limits above which measured Gini values can be considered reliable.