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The analysis of effective galaxies number count for Chinese Space Station Optical Survey(CSS-OS) by image simulation

Xin Zhang, Li Cao, Xianmin Meng

TL;DR

The paper evaluates the effective galaxy number density observable by the Chinese Space Station Optical Survey (CSS-OS) and compares it to LSST using image simulations rooted in HUDF galaxy catalogs. A dedicated image simulator integrates Sérsic galaxy profiles, PSF modeling, realistic SEDs, photometric redshifts, and instrument/noise characteristics to generate mock CSS-OS and LSST i-band images, from which galaxies are detected with SExtractor and matched to HUDF. Results show CSS-OS achieves about $13\,rac{arcmin^{-2}}$ (large-area) and $\sim40\,rac{arcmin^{-2}}$ (deep) detections, while LSST yields ~$42\,rac{arcmin^{-2}}$, with CSS-OS offering notable advantages in resolving small galaxies ($r_e<0.3''$) and producing distinct samples not recovered by LSST, especially in the deep survey. Overall, CSS-OS provides high-resolution insights into small, relatively low-redshift galaxies (mostly $z<0.8$), complementing LSST’s deeper reach for faint and larger galaxies, thereby informing survey strategy and joint science goals.

Abstract

The Chinese Space Station Optical Survey (CSS-OS) is a mission to explore the vast universe. This mission will equip a 2-meter space telescope to perform a multi-band NUV-optical large area survey (over 40% of the sky) and deep survey (~1% of the sky) for the cosmological and astronomical goals. Galaxy detection is one of the most important methods to achieve scientific goals. In this paper, we evaluate the galaxy number density for CSS-OS in i band (depth, i ~26 for large area survey and ~27 for the deep survey, point source, 5-sigma by the method of image simulation. We also compare galaxies detected by CSS-OS with that of LSST (i~27, point source, 5-sigma. In our simulation, the HUDF galaxy catalogs are used to create mock images due to long enough integration time which meets the completeness requirements of the galaxy analysis for CSS-OS and LSST. The galaxy surface profile and spectrum are produced by the morphological information, photometric redshift and SEDs from the catalogs. The instrumental features and the environmental condition are also considered to produce the mock galaxy images. The galaxies of CSS-OS and LSST are both extracted by SExtractor from the mock i band image and matched with the original catalog. Through the analysis of the extracted galaxies, we find that the effective galaxy number count is ~13 arcmin^-2, ~40 arcmin^-2 and ~42 arcmin^-2 for CSS-OS large area survey, CSS-OS deep survey and LSST, respectively. Moreover, CSS-OS shows the advantage in small galaxy detection with high spatial resolution, especially for the deep survey: about 20% of the galaxies detected by CSS-OS deep survey are not detected by LSST, and they have a small effective radius of re < 0.3".

The analysis of effective galaxies number count for Chinese Space Station Optical Survey(CSS-OS) by image simulation

TL;DR

The paper evaluates the effective galaxy number density observable by the Chinese Space Station Optical Survey (CSS-OS) and compares it to LSST using image simulations rooted in HUDF galaxy catalogs. A dedicated image simulator integrates Sérsic galaxy profiles, PSF modeling, realistic SEDs, photometric redshifts, and instrument/noise characteristics to generate mock CSS-OS and LSST i-band images, from which galaxies are detected with SExtractor and matched to HUDF. Results show CSS-OS achieves about (large-area) and (deep) detections, while LSST yields ~, with CSS-OS offering notable advantages in resolving small galaxies () and producing distinct samples not recovered by LSST, especially in the deep survey. Overall, CSS-OS provides high-resolution insights into small, relatively low-redshift galaxies (mostly ), complementing LSST’s deeper reach for faint and larger galaxies, thereby informing survey strategy and joint science goals.

Abstract

The Chinese Space Station Optical Survey (CSS-OS) is a mission to explore the vast universe. This mission will equip a 2-meter space telescope to perform a multi-band NUV-optical large area survey (over 40% of the sky) and deep survey (~1% of the sky) for the cosmological and astronomical goals. Galaxy detection is one of the most important methods to achieve scientific goals. In this paper, we evaluate the galaxy number density for CSS-OS in i band (depth, i ~26 for large area survey and ~27 for the deep survey, point source, 5-sigma by the method of image simulation. We also compare galaxies detected by CSS-OS with that of LSST (i~27, point source, 5-sigma. In our simulation, the HUDF galaxy catalogs are used to create mock images due to long enough integration time which meets the completeness requirements of the galaxy analysis for CSS-OS and LSST. The galaxy surface profile and spectrum are produced by the morphological information, photometric redshift and SEDs from the catalogs. The instrumental features and the environmental condition are also considered to produce the mock galaxy images. The galaxies of CSS-OS and LSST are both extracted by SExtractor from the mock i band image and matched with the original catalog. Through the analysis of the extracted galaxies, we find that the effective galaxy number count is ~13 arcmin^-2, ~40 arcmin^-2 and ~42 arcmin^-2 for CSS-OS large area survey, CSS-OS deep survey and LSST, respectively. Moreover, CSS-OS shows the advantage in small galaxy detection with high spatial resolution, especially for the deep survey: about 20% of the galaxies detected by CSS-OS deep survey are not detected by LSST, and they have a small effective radius of re < 0.3".

Paper Structure

This paper contains 17 sections, 14 equations, 16 figures, 5 tables.

Figures (16)

  • Figure 2: Pixel SNR comparison between HUDF and CSS-OS, LSST. Assuming the input signal is from a uniform extended source, so the PSF needn’t be considered in this calculation. The signal received by the detector can be obtained by aperture, total exposure time and telescope efficiency, then use the pixel size of the different telescope to normalize the received signal. The red solid line represents the ratio between HUDF pixel SNR normalized by CSS-OS pixel size and CSS-OS pixel SNR, and blue dashed line represents the ratio between HUDF pixel SNR normalized by LSST pixel size and LSST pixel SNR.
  • Figure 3: SED templates used in this paper which is from 2006AJ....132..926C. There are eight templates. The templates from El to Sb2 are given in 2004ApJS..150....1B and the other two more blue faint galaxies templates, 25 Myr and 5 Myr, are produced by BC03 (2003MNRAS.344.1000B). These SEDs consist of galaxies with different SFR histories.
  • Figure 4: The difference distribution between the photometric data and the simulation data from B, V, HUDF-z bands. Using the mock galaxies spectrum with the throughput of B, V, HUDF-z bands in Hubble telescope system, we can calculate the brightness of these bands.
  • Figure 5: Selected galaxies attributes. It shows the histogram of the effective radius(r$_e$), photometric redshift (photoz) and magnitude. The bin widths are 0.02, 0.1 and 0.2 respectively.
  • Figure 6: Mock images with HUDF catalog. Left: CSS-OS i band mock images. Right: LSST i band mock images. Top: The mock images produced by HUDF catalog whose area are 11.97 arcmin$^2$. Bottom: The enlarged views for the field of red box in top image whose area are about 0.5 arcmin$^2$.
  • ...and 11 more figures