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Buzzard to Cardinal: Improved Mock Catalogs for Large Galaxy Surveys

Authors :
To, Chun-Hao
DeRose, Joseph
Wechsler, Risa H.
Rykoff, Eli
Wu, Hao-Yi
Adhikari, Susmita
Krause, Elisabeth
Rozo, Eduardo
Weinberg, David H.
Publication Year :
2023

Abstract

We present the Cardinal mock galaxy catalogs, a new version of the Buzzard simulation that has been updated to support ongoing and future cosmological surveys, including DES, DESI, and LSST. These catalogs are based on a one-quarter sky simulation populated with galaxies out to a redshift of $z=2.35$ to a depth of $m_{\rm{r}}=27$. Compared to the Buzzard mocks, the Cardinal mocks include an updated subhalo abundance matching (SHAM) model that considers orphan galaxies and includes mass-dependent scatter between galaxy luminosity and halo properties. This model can simultaneously fit galaxy clustering and group--galaxy cross-correlations measured in three different luminosity threshold samples. The Cardinal mocks also feature a new color assignment model that can simultaneously fit color-dependent galaxy clustering in three different luminosity bins. We have developed an algorithm that uses photometric data to improve the color assignment model further and have also developed a novel method to improve small-scale lensing below the ray-tracing resolution. These improvements enable the Cardinal mocks to accurately reproduce the abundance of galaxy clusters and the properties of lens galaxies in the Dark Energy Survey data. As such, these simulations will be a valuable tool for future cosmological analyses based on large sky surveys. The cardinal mock will be released upon publication at https://chunhaoto.com/cardinalsim.<br />Comment: 37 pages; 20 figures. See figure 1 for summary and appendix K for a list of main differences between Cardinal and Buzzard. To be submitted to APJ; Comments welcome. Highlights can be found at https://chunhaoto.com/cardinalsim

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2303.12104
Document Type :
Working Paper