From Dark Matter to Galaxy Mocks

Cardinal consists of four key steps to convert dark matter-only simulations to galaxy survey mocks. The hierarchical nature of the method makes it possible to generate on the order of a hundred galaxy survey realizations in a manageable amount of time.

Improved Galaxy Model

Subhalo abundance matching (SHAM) is a technique that places galaxies on dark matter clumps (called halos) in the simulations. However, the first row of the plot shows that halos in the dark matter-only simulations do not look like halos in a universe with normal matter (baryons). Therefore, we develop a new SHAM model to fix this mismatch empirically and use new data to constrain the model.

Better galaxy clustering

Cardinal also features a new color assignment model. For the first time, the color-dependent galaxy clustering in mocks of its kind is statistically consistent with the measurement.

Corrected ray tracing

Cardinal uses a multi-plane ray-tracing technique (Calclens) to simulate gravitational lensing. Unfortunately, while the resolution of the ray tracing is high (~0.42'), the resolution effects show up at ~ 1 Mpc at z=0.6, preventing small-scale lensing analyses. Cardinal features a new algorithm to correct this effect, making small-scale lensing analyses possible.

Improved Photometry

Cardinal employs a conditional abundance matching technique to match the magnitude and color distribution of photometric survey data. The specially designed algorithm also makes properties of red sequence galaxies match data exquisitely.

Realistic galaxy clusters for the first time

Galaxy clusters are hard to simulate. Despite many works on this topic in the group, the number of galaxy clusters in Buzzard (the previous version, gray line) is half what we have in the data. With improved galaxy models, we can simulate realistic galaxy clusters (red line) for the first time!

Multi-purpose mock supports survey science

Cardinal mock and its predecessors are designed to support large galaxy survey science, including DES, DESI, LSST, and the Roman telescope. The realistic galaxy properties enable the production of several key tracers of the cosmic large-scale structure. These include but are not limited to redMaGiC galaxies, redMaPPer clusters, and weak lensing source galaxy samples. The main difference between Cardinal mock and other existing simulations is its low computational cost. One can generate hundreds of survey mocks to beat down cosmic variance.

Cardinal mocks are named after the Cardinal, which is the state bird of Ohio and also the name of Stanford sports teams. This name reflects the regions where the mocks were originally designed. The background image is an image simulation based on the Cardinal mock using the GalSim and Ngmix package.