No Arabic abstract
We have updated the Munich galaxy formation model to the Planck first-year cosmology, while modifying the treatment of baryonic processes to reproduce recent data on the abundance and passive fractions of galaxies from z= 3 down to z=0. Matching these more extensive and more precise observational results requires us to delay the reincorporation of wind ejecta, to lower the surface density threshold for turning cold gas into stars, to eliminate ram-pressure stripping in haloes less massive than ~10^14 Msun, and to modify our model for radio mode feedback. These changes cure the most obvious failings of our previous models, namely the overly early formation of low-mass galaxies and the overly large fraction of them that are passive at late times. The new model is calibrated to reproduce the observed evolution both of the stellar mass function and of the distribution of star formation rate at each stellar mass. Massive galaxies (M>10^11 [Msun]) assemble most of their mass before z=1 and are predominantly old and passive at z=0, while lower mass galaxies assemble later and, for M<10^9.5 (Msun), are still predominantly blue and star forming at z=0. This phenomenological but physically based model allows the observations to be interpreted in terms of the efficiency of the various processes that control the formation and evolution of galaxies as a function of their stellar mass, gas content, environment and time.
We investigate the evolution of galaxy masses and star formation rates in the Evolution and Assembly of Galaxies and their Environment (EAGLE) simulations. These comprise a suite of hydrodynamical simulations in a $Lambda$CDM cosmogony with subgrid models for radiative cooling, star formation, stellar mass loss, and feedback from stars and accreting black holes. The subgrid feedback was calibrated to reproduce the observed present-day galaxy stellar mass function and galaxy sizes. Here we demonstrate that the simulations reproduce the observed growth of the stellar mass density to within 20 per cent. The simulation also tracks the observed evolution of the galaxy stellar mass function out to redshift z = 7, with differences comparable to the plausible uncertainties in the interpretation of the data. Just as with observed galaxies, the specific star formation rates of simulated galaxies are bimodal, with distinct star forming and passive sequences. The specific star formation rates of star forming galaxies are typically 0.2 to 0.4 dex lower than observed, but the evolution of the rates track the observations closely. The unprecedented level of agreement between simulation and data makes EAGLE a powerful resource to understand the physical processes that govern galaxy formation.
Star-formation activity is a key property to probe the structure formation and hence characterise the large-scale structures of the universe. This information can be deduced from the star formation rate (SFR) and the stellar mass (Mstar), both of which, but especially the SFR, are very complex to estimate. Determining these quantities from UV, optical, or IR luminosities relies on complex modeling and on priors on galaxy types. We propose a method based on the machine-learning algorithm Random Forest to estimate the SFR and the Mstar of galaxies at redshifts in the range 0.01<z<0.3, independent of their type. The machine-learning algorithm takes as inputs the redshift, WISE luminosities, and WISE colours in near-IR, and is trained on spectra-extracted SFR and Mstar from the SDSS MPA-JHU DR8 catalogue as outputs. We show that our algorithm can accurately estimate SFR and Mstar with scatters of sigma_SFR=0.38 dex and sigma_Mstar=0.16 dex for SFR and stellar mass, respectively, and that it is unbiased with respect to redshift or galaxy type. The full-sky coverage of the WISE satellite allows us to characterise the star-formation activity of all galaxies outside the Galactic mask with spectroscopic redshifts in the range 0.01<z<0.3. The method can also be applied to photometric-redshift catalogues, with best scatters of sigma_SFR=0.42 dex and sigma_Mstar=0.24 dex obtained in the redshift range 0.1<z<0.3.
We adapt the L-Galaxies semi-analytic model to follow the star-formation histories (SFH) of galaxies -- by which we mean a record of the formation time and metallicities of the stars that are present in each galaxy at a given time. We use these to construct stellar spectra in post-processing, which offers large efficiency savings and allows user-defined spectral bands and dust models to be applied to data stored in the Millennium data repository. We contrast model SFHs from the Millennium Simulation with observed ones from the VESPA algorithm as applied to the SDSS-7 catalogue. The overall agreement is good, with both simulated and SDSS galaxies showing a steeper SFH with increased stellar mass. The SFHs of blue and red galaxies, however, show poor agreement between data and simulations, which may indicate that the termination of star formation is too abrupt in the models. The mean star-formation rate (SFR) of model galaxies is well-defined and is accurately modelled by a double power law at all redshifts: SFR proportional to $1/(x^{-1.39}+x^{1.33})$, where $x=(t_a-t)/3.0,$Gyr, $t$ is the age of the stars and $t_a$ is the loopback time to the onset of galaxy formation; above a redshift of unity, this is well approximated by a gamma function: SFR proportional to $x^{1.5}e^{-x}$, where $x=(t_a-t)/2.0,$Gyr. Individual galaxies, however, show a wide dispersion about this mean. When split by mass, the SFR peaks earlier for high-mass galaxies than for lower-mass ones, and we interpret this downsizing as a mass-dependence in the evolution of the quenched fraction: the SFHs of star-forming galaxies show only a weak mass dependence.
We examine the growth of the stellar content of galaxies from z=3-0 in cosmological hydrodynamic simulations incorporating parameterised galactic outflows. Without outflows, galaxies overproduce stellar masses (M*) and star formation rates (SFRs) compared to observations. Winds introduce a three-tier form for the galaxy stellar mass and star formation rate functions, where the middle tier depends on differential (i.e. mass-dependent) recycling of ejected wind material back into galaxies. A tight M*-SFR relation is a generic outcome of all these simulations, and its evolution is well-described as being powered by cold accretion, although current observations at z>2 suggest that star formation in small early galaxies must be highly suppressed. Roughly one-third of z=0 galaxies at masses below M^* are satellites, and star formation in satellites is not much burstier than in centrals. All models fail to suppress star formation and stellar mass growth in massive galaxies at z<2, indicating the need for an external quenching mechanism such as black hole feedback. All models also fail to produce dwarfs as young and rapidly star-forming as observed. An outflow model following scalings expected for momentum-driven winds broadly matches observed galaxy evolution around M^* from z=0-3, which is a significant success since these galaxies dominate cosmic star formation, but the failures at higher and lower masses highlight the challenges still faced by this class of models. We argue that central star-forming galaxies are well-described as living in a slowly-evolving equilibrium between inflows from gravity and recycled winds, star formation, and strong and ubiquitous outflows that regulate how much inflow forms into stars. Star-forming galaxy evolution is thus primarily governed by the continual cycling of baryons between galaxies and intergalactic gas.
We show that a model consisting of individual, log-normal star formation histories for a volume-limited sample of $zapprox0$ galaxies reproduces the evolution of the total and quiescent stellar mass functions at $zlesssim2.5$ and stellar masses $M_*geq10^{10},{rm M_odot}$. This model has previously been shown to reproduce the star formation rate/stellar mass relation (${rm SFR}$--$M_*$) over the same interval, is fully consistent with the observed evolution of the cosmic ${rm SFR}$ density at $zleq8$, and entails no explicit quenching prescription. We interpret these results/features in the context of other models demonstrating a similar ability to reproduce the evolution of (1) the cosmic ${rm SFR}$ density, (2) the total/quiescent stellar mass functions, and (3) the ${rm SFR}$--$M_*$ relation, proposing that the key difference between modeling approaches is the extent to which they stress/address diversity in the (starforming) galaxy population. Finally, we suggest that observations revealing the timescale associated with dispersion in ${rm SFR}(M_*)$ will help establish which models are the most relevant to galaxy evolution.