2019ApJ...872..180C

Halo merger trees are constructed from ELUCID, a constrained N-body simulation in the Sloan Digital Sky Survey (SDSS) volume. These merger trees are used to populate dark matter halos with galaxies according to an empirical model of galaxy formation. Mock catalogs in the SDSS sky coverage are constructed, which can be used to study the spatial distribution of galaxies in the low-z universe. These mock catalogs are used to quantify the cosmic variance (CV) in the galaxy stellar mass function (GSMF) measured from the SDSS survey. The GSMF estimated from the SDSS magnitude-limited sample can be affected significantly by the presence of an underdense region at z < 0.03, so that the low-mass end of the function can be underestimated significantly. Several existing methods designed to deal with the effects of the CV in the estimate of the GSMF are tested, and none is found to be able to fully account for the CV. We propose a method based on conditional stellar mass functions in dark matter halos, which can provide an unbiased estimate of the global GSMF. The application of the method to SDSS data shows that the GSMF has a significant upturn at M_* < 10_9.5h^–1M_☉, which has been missed in many earlier measurements of the local GSMF.