A semi-analytical mock galaxy catalog for the CSST extragalactic surveys from the Jiutian simulations

TL;DR

This paper presents a semi-analytical mock galaxy catalog for the CSST surveys, generated from Jiutian simulations, incorporating detailed galaxy properties and observational predictions up to redshift 5.

Contribution

The work introduces a comprehensive mock galaxy catalog using advanced simulation coupling, neural network SED modeling, and optimized light-cone construction for the CSST surveys.

Findings

Catalog reproduces observed galaxy properties across mass and redshift.

Good convergence between different simulation resolutions.

Accurately predicts galaxy distributions for CSST observations.

Abstract

We introduce a mock galaxy catalog built for the CSST extragalactic surveys using the primary runs of the Jiutian $N$-body simulation suites. The catalogs are built by coupling the GAlaxy Evolution and Assembly (GAEA) semi-analytical model of galaxy formation with merger trees extracted from the simulations using the Hierarchical Bound-Tracing (HBT+) algorithm. The spectral energy distributions (SEDs) and broadband magnitudes are computed using the neural-network-based stellar population synthesizer StarDuster, which is trained on radiative transfer simulations to account for detailed galaxy geometry in modeling dust obscuration. Galaxy light-cones up to $z=5$ are subsequently generated with the BLiC light-cone builder which interpolates the properties of galaxies over time using an optimized interpolation scheme. The resulting catalogs exhibit good convergence in many statistical properties of the galaxy population produced from two different resolution simulations. The catalogs reproduce a number of observed galaxy properties across a range of galaxy mass and redshift, including the stellar mass functions, the luminosity function, gas mass fraction, galaxy size-mass relation and galaxy clustering. We also present the photometric and redshift distributions of galaxies expected to be observed in the CSST surveys.