Evaluating the Accuracy of Non-parametric Galaxy Morphological Indicator Measurements in the CSST Imaging Survey
Yuchong Luo, Anhe Sha, Jian Ren, Xin Zhang, Xianmin Meng, Nan Li, and F.S. Liu

TL;DR
This study assesses CSST's ability to detect and accurately measure galaxy morphologies using non-parametric indicators, comparing its performance to HST and providing correction methods for wide and deep surveys.
Contribution
It introduces correction functions for CSST morphological measurements, enabling consistent galaxy classification with HST data.
Findings
CSST deep surveys match HST in galaxy detection capabilities.
Wide-field CSST surveys have biases in detecting low-surface-brightness galaxies.
Correction functions improve measurement accuracy for CSST data.
Abstract
The Chinese Space Station Telescope (CSST) is China's upcoming next-generation ultraviolet and optical survey telescope, with imaging resolution capabilities comparable to the Hubble Space Telescope (HST). In this study, we utilized a comprehensive sample of 3,679 CSST realistic mock galaxies constructed from HST CANDELS/GOODS-North deep imaging observations, with stellar masses and redshifts . We evaluate the detection capabilities of CSST surveys and the accuracy in measuring the non-parametric morphological indicators (, , , , , ) of galaxies. Our findings show that in terms of galaxy detection capabilities, CSST's deep field surveys can achieve the same level as HST's deep field observations; however, in wide-field surveys, CSST exhibits a significant deficiency in detecting…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
