Ginevra Fabole
(Instituto de Física Teórica, Madrid)
Star-forming galaxies as tools for cosmology in next-generation redshift surveys
High-volume redshift surveys, as the Sloan Digital Sky Survey (SDSS) and the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) targeted a bluer starforming population of galaxies that is still little known, compared to the luminous red galaxy sample typically used for clustering studies. We quantify the differences between these two populations at z > 0.55 in BOSS CMASS DR11, in terms of clustering, bias and redshift-space distortions to understand how significant they are, and reproduce them in mock catalogs using a standard Halo Occupation Distribution (HOD) approach. In the specific case of emission line galaxies (ELGs) i.e., UV-selected starforming galaxies, the traditional HOD or (Sub)Halo Abundance Matching methods cannot be applied, since the sample is highly incomplete in stellar mass. Next-generation surveys, as SDSS-IV/eBOSS and DESI, will use ELGs as BAO tracers to explore the large scale structure of the Universe out to redshift z ∼ 2. Observing ELGs, learning how to model their clustering properties and understanding how they populate their host halos are therefore crucial points that we need to address to link observations to cosmology. To this purpose, we present a modified SHAM prescription, directly based on the latest MultiDark Planck N-body simulation, that accounts for the ELG incompleteness and accurately predicts the ELG clustering both on small and large scales.