The first comprehensive Milky Way stellar mock catalogue for the Chinese Space Station Telescope Survey Camera

TL;DR

This paper presents the first comprehensive Milky Way stellar mock catalogue tailored for the Chinese Space Station Telescope's survey camera, supporting future data analysis and survey planning.

Contribution

It introduces a detailed mock catalogue of 12.6 billion stars for the CSST, aiding in understanding Milky Way populations and survey optimization.

Findings

Catalogue includes stars down to g=27.5 mag.

Supports comparison with future CSST survey data.

Provides insights into faint stellar populations.

Abstract

The Chinese Space Station Telescope (CSST) is a cutting-edge two-meter astronomical space telescope currently under construction. Its primary Survey Camera (SC) is designed to conduct large-area imaging sky surveys using a sophisticated seven-band photometric system. The resulting data will provide unprecedented data for studying the structure and stellar populations of the Milky Way. To support the CSST development and scientific projects related to its survey data, we generate the first comprehensive Milky Way stellar mock catalogue for the CSST SC photometric system using the TRILEGAL stellar population synthesis tool. The catalogue includes approximately 12.6 billion stars, covering a wide range of stellar parameters, photometry, astrometry, and kinematics, with magnitude reaching down to $g\,=\,27.5$ mag in the AB magnitude system. The catalogue represents our benchmark understanding of the stellar populations in the Milky Way, enabling a direct comparison with the future CSST survey data. Particularly, it sheds light on faint stars that are hidden from current sky surveys. Our crowding limit analysis based on this catalogue provides compelling evidence for the extension of the CSST Optical Survey (OS) to cover low Galactic latitude regions. The strategic extension of the CSST-OS coverage, combined with this comprehensive mock catalogue, will enable transformative science with the CSST.