Tiago Costa, Debora Sijacki, Michele Trenti, Martin Haehnelt
We employ cosmological hydrodynamical simulations to investigate models in which the supermassive black holes (BHs) powering luminous z ~ 6 QSOs grow from massive seeds. We simulate at high resolution 18 fields sampling regions with densities ranging from the mean cosmic density all the way to the highest sigma peaks in the Millennium simulation volume. Only in the most massive halos, BHs can grow to masses up to ~ 10^9 Msun by z ~ 6 without invoking super-Eddington accretion. Accretion onto the most massive BHs becomes limited by thermal AGN feedback by z ~ 9-8 with further BH growth proceeding in short Eddington limited bursts. Our modelling suggests that current flux-limited surveys of QSOs at high redshift preferentially detect objects at their peak luminosity and therefore miss a substantial population of QSOs powered by similarly massive BHs but with low accretion rates. To test whether the required host halo masses are consistent with the observed galaxy environment of z ~ 6 QSOs, we produce realistic rest-frame UV images of our simulated galaxies. Without strong stellar feedback, our simulations predict numbers of bright galaxies larger than observed by a factor ten or more. Supernova-driven galactic winds reduce the predicted numbers to a level consistent with observations indicating that stellar feedback was already very efficient at high redshifts. We have further investigated the effect of thermal AGN feedback on the surrounding gas. Our adopted AGN feedback prescription drives mostly energy-driven highly anisotropic outflows with gas speeds of >= 1000 km/s to distances of >= 10 kpc consistent with observations. The spatially extended thermal X-ray emission around bright QSOs powered by these outflows can exceed by large factors the emission expected without AGN feedback and is an important diagnostic of the mechanism whereby AGN feedback energy couples to surrounding gas.
View original:
http://arxiv.org/abs/1307.5854
No comments:
Post a Comment