No Arabic abstract
We compare the predictions of three independently developed semi-analytic galaxy formation models that are being used to aid in the interpretation of results from the CANDELS survey. These models are each applied to the same set of halo merger trees extracted from the Bolshoi simulation and are carefully tuned to match the local galaxy stellar mass function using the powerful method of Bayesian Inference coupled with MCMC or by hand. The comparisons reveal that in spite of the significantly different parameterizations for star formation and feedback processes, the three models yield qualitatively similar predictions for the assembly histories of galaxy stellar mass and star formation over cosmic time. We show that the SAMs generally require strong outflows to suppress star formation in low-mass halos to match the present day stellar mass function. However, all of the models considered produce predictions for the star formation rates and metallicities of low-mass galaxies that are inconsistent with existing data and diverge between the models. We suggest that large differences in the metallicity relations and small differences in the stellar mass assembly histories of model galaxies stem from different assumptions for the outflow mass-loading factor. Importantly, while more accurate observational measurements for stellar mass, SFR and metallicity of galaxies at 1<z<5 will discriminate between models, the discrepancies between the models and existing data of these observables have already revealed challenging problems in understanding star formation and its feedback in galaxy formation. The three sets of models are being used to construct catalogs of mock galaxies on light cones that have the same geometry as the CANDELS survey, which should be particularly useful for quantifying the biases and uncertainties on measurements and inferences from the real observations. -ABRIDGED
In this work, we compare large scale structure observables for stellar mass selected samples at $z=0$, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo paramaters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy-halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher-order statistics, such as cumulants of the density field, help to accurately describe the galaxy distribution and discriminate between models that show degenerate behavior for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.
We study the probability distribution function (PDF) of relative velocity between two different dark matter halos (i.e. pairwise velocity) with a set of high-resolution cosmological $N$-body simulations. We investigate the pairwise velocity PDFs over a wide range of halo masses of $10^{12.5-15}, h^{-1}M_{odot}$ and redshifts of $0<z<1$. At a given set of masses, redshift and the separation length between two halos, our model requires three parameters to set the pairwise velocity PDF, whereas previous non-Gaussian models in the literature assume four or more free parameters. At the length scales of $r=5-40, [h^{-1}, mathrm{Mpc}]$, our model predicts the mean and dispersion of the pairwise velocity for dark matter halos with their masses of $10^{12.5-13.5} , [h^{-1}M_{odot}]$ at $0.3 < z < 1$ with a 5%-level precision, while the model precision reaches a 20% level (mostly a 10% level) for other masses and redshifts explored in the simulations. We demonstrate that our model of the pairwise velocity PDF provides an accurate mapping of the two-point clustering of massive-galaxy-sized halos at the scales of $O(10), h^{-1}mathrm{Mpc}$ between redshift and real space for a given real-space correlation function. For a mass-limited halo sample with their masses greater than $10^{13.5}, h^{-1}M_{odot}$ at $z=0.55$, our model can explain the monopole and quadropole moments of the redshift-space two-point correlations with a precision better than 5% at the scales of $5-40$ and $10-30, h^{-1}mathrm{Mpc}$, respectively. Our model of the pairwise velocity PDF will give a detailed explanation of statistics of massive galaxies at the intermediate scales in redshift surveys, including the non-linear redshift-space distortion effect in two-point correlation functions and the measurements of the kinematic Sunyaev-Zeldovich effect.
We examine the spheroid growth and star formation quenching experienced by galaxies from z~3 to the present by studying the evolution with redshift of the quiescent and spheroid-dominated fractions of galaxies from the CANDELS and GAMA surveys. We compare the observed fractions with predictions from a semi-analytic model which includes prescriptions for bulge growth and AGN feedback due to mergers and disk instabilities. We facilitate direct morphological comparison by converting our model bulge-to-total stellar mass ratios to Sersic indices. We then subdivide our population into the four quadrants of the sSFR-Sersic index plane and study the buildup of each of these subpopulations. We find that the fraction of star forming disks declines steadily, while the fraction of quiescent spheroids builds up over cosmic time. The fractions of star forming spheroids and quiescent disks are both non-negligible, and stay nearly constant over the period we have studied, at about 10% and 15-20% respectively. Our model is qualitatively successful at reproducing the evolution of the two main populations (star forming disk-dominated galaxies and quiescent spheroid-dominated galaxies), and approximately reproduces the relative fractions of all four types, but predicts a stronger decline in star forming spheroids, and increase in quiescent disks, than seen in the observations. A model with an additional channel for bulge growth via disk instabilities agrees better overall with the observations than a model in which bulges may grow only through mergers. We study evolutionary tracks of some individual galaxies as they experience morphological transformation and quenching, and examine the importance of different physical drivers of this transformation (major and minor mergers and disk instabilities). We find that complex histories with multiple transformative events are the norm.
We introduce a new physical recipe into the De Lucia and Blaizot version of the Munich semi-analytic model built upon the Millennium dark matter simulation: the tidal stripping of stellar material from satellite galaxies during mergers. To test the significance of the new physical process we apply a Monte Carlo Markov Chain parameter estimation technique constraining the model with the $K$-band luminosity function, $B-V$ colours and the black hole-bulge mass relation. The differences in parameter correlations, and in the allowed regions in likelihood space, reveal the impact of the new physics on the basic ingredients of the model, such as the star-formation laws, feedback recipes and the black hole growth model. With satellite disruption in place, we get a model likelihood four times higher than in the original model, indicating that the new process seems to be favoured by observations. This is achieved mainly due to a reduction in black hole growth that produces a better agreement between the properties of central black holes and host galaxies. Compared to the best-fit model without disruption, the new model removes the excess of dwarf galaxies in the original recipe with a more modest supernova heating. The new model is now consistent with the three observational data sets used to constrain it, while significantly improving the agreement with observations for the distribution of metals in stars. Moreover, the model now follows the build up of intra-cluster light.
We compare the semi-analytic models of galaxy formation of Fu et al. (2010), which track the evolution of the radial profiles of atomic and molecular gas in galaxies, with gas fraction scaling relations derived from the COLD GASS survey (Saintonge et al 2011). The models provide a good description of how condensed baryons in galaxies with gas are partitioned into stars, atomic and molecular gas as a function of galaxy stellar mass and surface density. The models do not reproduce the tight observed relation between stellar surface density and bulge-to-disk ratio for this population. We then turn to an analysis of thequenched population of galaxies without detectable cold gas. The current implementation of radio-mode feedback in the models disagrees strongly with the data. In the models, gas cooling shuts down in nearly all galaxies in dark matter halos above a mass of 10**12 M_sun. As a result, stellar mass is the observable that best predicts whether a galaxy has little or no neutral gas. In contrast, our data show that quenching is largely independent of stellar mass. Instead, there are clear thresholds in bulge-to-disk ratio and in stellar surface density that demarcate the location of quenched galaxies. We propose that processes associated with bulge formation play a key role in depleting the neutral gas in galaxies and that further gas accretion is suppressed following the formation of the bulge, even in dark matter halos of low mass.