No Arabic abstract
We show the significance of the super-Eddington accretion for the cosmic growth of supermassive black holes (SMBHs) with a semi-analytical model for galaxy and black hole evolution. The model explains various observed properties of galaxies and active galactic nuclei at a wide redshift range. By tracing the growth history of individual SMBHs, we find that the fraction of the SMBH mass acquired during the super-Eddington accretion phases to the total SMBH mass becomes larger for less massive black holes and at higher redshift. Even at z = 0, SMBHs with > 1e+9 Msun have acquired more than 50% of their mass by super-Eddington accretions, which is apparently inconsistent with classical Soltans argument. However, the mass-weighted radiation efficiency of SMBHs with > 1e+8 Msun obtained with our model, is about 0.08 at z = 0, which is consistent with Soltans argument within the observational uncertainties. We, therefore, conclude that Soltans argument cannot reject the possibility that SMBHs are grown mainly by super-Eddington accretions.
We present a simple semi-numerical model designed to explore black hole growth and galaxy evolution. This method builds on a previous model for black hole accretion that uses a semi-numerical galaxy formation model and universal Eddington ratio distribution to describe the full AGN population by independently connecting galaxy and AGN growth to the evolution of the host dark matter halos. We fit observed X-ray luminosity functions up to a redshift of z ~ 4, as well as investigate the evolution of the Eddington ratio distributions. We find that the Eddington ratio distribution evolves with redshift such that the slope of the low-Eddington accretion rate distribution increases with cosmic time, consistent with the behavior predicted in hydrodynamical simulations for galaxies with different gas fractions. We also find that the evolution of our average Eddington ratio is correlated with observed star formation histories, supporting a picture in which black holes and galaxies evolve together in a global sense. We further confirm the impact of luminosity limits on observed galaxy and halo properties by applying selection criteria to our fiducial model and comparing to surveys across a wide range of redshifts.
Supermassive black hole (SMBH) binaries residing at the core of merging galaxies are recently found to be strongly affected by the rotation of their host galaxies. The highly eccentric orbits that form when the host is counterrotating emit strong bursts of gravitational waves that propel rapid SMBH binary coalescence. Most prior work, however, focused on planar orbits and a uniform rotation profile, an unlikely interaction configuration. However, the coupling between rotation and SMBH binary evolution appears to be such a strong dynamical process that it warrants further investigation. This study uses direct N-body simulations to isolate the effect of galaxy rotation in more realistic interactions. In particular, we systematically vary the SMBH orbital plane with respect to the galaxy rotation axis, the radial extent of the rotating component, and the initial eccentricity of the SMBH binary orbit. We find that the initial orbital plane orientation and eccentricity alone can change the inspiral time by an order of magnitude. Because SMBH binary inspiral and merger is such a loud gravitational wave source, these studies are critical for the future gravitational wave detector, LISA, an ESA/NASA mission currently set to launch by 2034.
By means of our own cosmological-hydrodynamical simulation and semi-analytical model we studied galaxy population properties in clusters and groups, spanning over 10 different bands from UV to NIR, and their evolution since redshift z=2. We compare our results in terms of galaxy red/blue fractions and luminous-to-faint ratio (LFR) on the Red Sequence (RS) with recent observational data reaching beyond z=1.5. Different selection criteria were tested in order to retrieve galaxies belonging to the RS: either by their quiescence degree measured from their specific SFR (Dead Sequence), or by their position in a colour-colour plane which is also a function of sSFR. In both cases, the colour cut and the limiting magnitude threshold were let evolving with redshift, in order to follow the natural shift of the characteristic luminosity in the LF. We find that the Butcher-Oemler effect is wavelength-dependent, with the fraction of blue galaxies increasing steeper in optical colours than in NIR. Besides, only when applying a lower limit in terms of fixed absolute magnitude, a steep BO effect can be reproduced, while the blue fraction results less evolving when selecting samples by stellar mass or an evolving magnitude limit. We then find that also the RS-LFR behaviour, highly debated in the literature, is strongly dependent on the galaxy selection function: in particular its very mild evolution recovered when measured in terms of stellar mass, is in agreement with values reported for some of the highest redshift confirmed (proto)clusters. As to differences through environments, we find that normal groups and (to a lesser extent) cluster outskirts present the highest values of both star forming fraction and LFR at low z, while fossil groups and cluster cores the lowest: this separation among groups begins after z~0.5, while earlier all group star forming properties are undistinguishable.
The co-evolution of supermassive black holes (SMBHs) with their host galaxies remains to be fully explored, especially at high redshift. While often understood as a consequence of self-regulation via AGN feedback, it may also be explained by alternative SMBH accretion models. Here, we expand on previous work by studying the growth of SMBHs with the help of a large suite of cosmological zoom-in simulations (textsc{small{MassiveFIRE}}) that are part of the Feedback in Realistic Environments (FIRE) project. The growth of SMBHs is modeled in post-processing with different accretion models, placements, and merger treatments, and validated by comparing to on-the-fly calculations. Scaling relations predicted by the gravitational torque driven accretion (GTDA) model agree with observations at low redshift emph{without} the need for AGN feedback, in contrast to models in which the accretion rate depends strongly on SMBH mass. At high redshift, we find deviations from the local scaling relations in line with previous results. In particular, SMBHs are under-massive, presumably due to stellar feedback, but start to grow efficiently once their host galaxies reach $M_* sim 10^{10} M_{odot}$. We analyze and explain these findings in the context of a simple analytic model. Finally, we show that the predicted scaling relations depend sensitively on the efficiency of SMBH merging. These findings highlight the relevance of understanding the evolution of SMBH-galaxy scaling relations to predict the rate of gravitational wave signals from SMBH mergers across cosmic history.
We implement a sample-efficient method for rapid and accurate emulation of semi-analytical galaxy formation models over a wide range of model outputs. We use ensembled deep learning algorithms to produce a fast emulator of an updated version of the GALFORM model from a small number of training examples. We use the emulator to explore the models parameter space, and apply sensitivity analysis techniques to better understand the relative importance of the model parameters. We uncover key tensions between observational datasets by applying a heuristic weighting scheme in a Markov chain Monte Carlo framework and exploring the effects of requiring improved fits to certain datasets relative to others. Furthermore, we demonstrate that this method can be used to successfully calibrate the model parameters to a comprehensive list of observational constraints. In doing so, we re-discover previous GALFORM fits in an automatic and transparent way, and discover an improved fit by applying a heavier weighting to the fit to the metallicities of early-type galaxies. The deep learning emulator requires a fraction of the model evaluations needed in similar emulation approaches, achieving an out-of-sample mean absolute error at the knee of the K-band luminosity function of 0.06 dex with less than 1000 model evaluations. We demonstrate that this is an extremely efficient, inexpensive and transparent way to explore multi-dimensional parameter spaces, and can be applied more widely beyond semi-analytical galaxy formation models.