Khostovan, Ali Ahmad and Sobral, David and Mobasher, Bahram and Best, Philip N. and Smail, Ian and Matthee, Jorryt and Darvish, Behnam and Nayyeri, Hooshang and Hemmati, Shoubaneh and Stott, John P. (2018) The clustering of H β + [O III] and [O II] emitters since z ∼ 5 : dependencies with line luminosity and stellar mass. Monthly Notices of the Royal Astronomical Society, 478 (3). 2999–3015. ISSN 0035-8711
Abstract
We investigate the clustering properties of ∼7000 H β + [O III] and [O II] narrowband-selected emitters at z ∼ 0.8–4.7 from the High-z Emission Line Survey. We find clustering lengths, r0, of 1.5–4.0 h−1 Mpc and minimum dark matter halo masses of 1010.7–12.1 M⊙ for our z = 0.8–3.2 H β + [O III] emitters and r0 ∼ 2.0–8.3 h−1 Mpc and halo masses of 1011.5–12.6 M⊙ for our z = 1.5–4.7 [O II] emitters. We find r0 to strongly increase both with increasing line luminosity and redshift. By taking into account the evolution of the characteristic line luminosity, L⋆(z), and using our model predictions of halo mass given r0, we find a strong, redshift-independent increasing trend between L/L⋆(z) and minimum halo mass. The faintest H β + [O III] emitters are found to reside in 109.5 M⊙ haloes and the brightest emitters in 1013.0 M⊙ haloes. For [O II] emitters, the faintest emitters are found in 1010.5 M⊙ haloes and the brightest emitters in 1012.6 M⊙ haloes. A redshift-independent stellar mass dependency is also observed where the halo mass increases from 1011 to 1012.5 M⊙ for stellar masses of 108.5 to 1011.5 M⊙, respectively. We investigate the interdependencies of these trends by repeating our analysis in a Lline−Mstar grid space for our most populated samples (H β + [O III] z = 0.84 and [O II] z = 1.47) and find that the line luminosity dependency is stronger than the stellar mass dependency on halo mass. For L > L⋆ emitters at all epochs, we find a relatively flat trend with halo masses of 1012.5–13 M⊙, which may be due to quenching mechanisms in massive haloes that is consistent with a transitional halo mass predicted by models.