Measuring Structural Parameters Through Stacking Galaxy Images
Yubin Li, XianZhong Zheng, Qiu-Sheng Gu, Yi-Peng Wang, ZhangZheng Wen,, Kexin Guo, FangXia An

TL;DR
This paper evaluates the effectiveness of galaxy image stacking in recovering average structural parameters of faint high-redshift galaxies, highlighting biases and correction methods for accurate measurements.
Contribution
It introduces a simulation-based analysis of stacking techniques to quantify biases in recovering galaxy structural parameters, providing correction strategies.
Findings
Stacking can accurately recover mean galaxy profiles with biases.
Inclined galaxies cause overestimation of Sersic index and underestimation of Re.
Biases depend on the distributions of Re, AR, and n in galaxy samples.
Abstract
It remains challenging to detect the low surface brightness structures of faint high-z galaxies, which is key to understanding the structural evolution of galaxies. The technique of image stacking allows us to measure the averaged light profile beneath the detection limit and probe the extended structure of a group of galaxies. We carry out simulations to examine the recovery of the averaged surface brightness profile through stacking model HST/ACS images of a set of galaxies as functions of Sersic index (n), effective radius (Re) and axis ratio (AR). The Sersic profile best fitting the radial profile of the stacked image is taken as the recovered profile, in comparison with the intrinsic mean profile of the model galaxies. Our results show that, in general, the structural parameters of the mean profile can be properly determined through stacking, although systematic biases need to be…
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