Speaker
Description
In ongoing and future cosmological surveys, such as DESI, PFS, Euclid, CSST, and WFIRST, ELGs are a critically major tracer to explore the acceleration of the cosmic expansion and to test modified gravity theories. To achieve the high-precision observations aimed by the surveys on the Hubble parameter, cosmic growth rate and neutrino mass etc, one needs to have an accurate understanding of the connection between ELGs and dark matter halos. Because of the complicated target selections both in color and in magnitude, the population of ELGs is expected to change significantly with redshift, which makes the parameters of HOD always changing with redshift. We propose a novel method (Gao et al; Paper I) to construct the relation. In this method, after the relation is established for galaxies in the whole population (i.e. normal galaxies), the ELGs can be obtained by a random selection based on the observed number density once the probability Psat of a satellite galaxy becoming an ELG is reasonably reduced. We have applied the method to DESI SV3 (or 1 Percent Sample) survey, and found it very successful. With only 7-parameters, we can accurately describe the clustering of ELGs both in real and redshift spaces at all redshift range (0.8<z<1.5; Gao et al. Paper II). We also demonstrate that galaxy conformity is necessary and easy to be implemented in the framework to accurately describe the small-scale clustering of ELGs in DESI SV3 (Gao et al, Paper III). Compared with HOD models in literature, our method has only a minimal set of parameters (8 when galaxy conformity is included), has clear physical meaning (Psat is reduced; galaxy conformity), is universal for all redshift range, and is accurate for describing clustering from 0.010 Mpc/h up to large scales.
