Mock Observations for the CSST Mission: Main Surveys -- the Mock Catalogue

TL;DR

This paper presents a comprehensive mock catalogue of stars and galaxies designed for the CSST mission, supporting image simulations and cosmological analyses by providing detailed properties validated against observational data.

Contribution

The authors developed a detailed, validated mock catalogue for the CSST mission, including galaxy properties, lensing effects, and spectral energy distributions, to aid in image processing and scientific studies.

Findings

Mock catalogue shows good agreement with observational data.

Supports multi-band imaging and spectroscopic simulations.

Enables diverse cosmological analyses for CSST.

Abstract

The Chinese Space Station Survey Telescope (CSST) is a flagship space mission, designed to carry out a large-area sky survey to explore the nature of dark matter and dark energy in the Universe. The onboard multi-band imaging and slitless spectroscopic modules will enable us to obtain photometric data for billions of galaxies and stars, as well as hundreds of millions of spectroscopic measurements, advancing various scientific analyses such as galaxy clustering and weak gravitational lensing. To support the image simulations for the main survey of the CSST mission, we present a mock catalogue of stars and galaxies. For stars, the mock catalogue is generated using either Galaxia or TRILEGAL, both of which provide a range of stellar properties to meet the requirements of CSST image simulations. For galaxies, we built a mock light-cone up to redshift z~3.5 from the cosmological Nbody simulation and populated the mock galaxy catalogue from the dark mater haloes using a semi-analytical galaxy formation model. We then performed a full-sky ray-tracing simulation of weak gravitational lensing to obtain lensing shear at the position of each galaxy in the light-cone. To support both multi-band imaging and slitless spectroscopic simulations, we computed the spectral energy distribution (SED) for each galaxy based on its star formation history using a supervised deep-learning model and determined the magnitudes in each band using the CSST throughputs. Finally, the properties of our mock galaxies include positions, redshifts, stellar masses, shapes, sizes, SEDs, lensing shears and magnifications. We have validated our mock catalogue against observational data and theoretical models, with results showing good overall agreement. The catalogue provides a flexible dataset for the development of CSST image processing and can support a wide range of cosmological analyses within the CSST mission.