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Register a new userEvolution of galaxy stellar masses and star formation rates in the EAGLE simulations
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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.
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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 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.
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.
To understand cosmic mass assembly in the Universe at early epochs, we primarily rely on measurements of stellar mass and star formation rate of distant galaxies. In this paper, we present stellar masses and star formation rates of six high-redshift ($2.8leq z leq 5.7$) dusty, star-forming galaxies (DSFGs) that are strongly gravitationally lensed by foreground galaxies. These sources were first discovered by the South Pole Telescope (SPT) at millimeter wavelengths and all have spectroscopic redshifts and robust lens models derived from ALMA observations. We have conducted follow-up observations, obtaining multi-wavelength imaging data, using {it HST}, {it Spitzer}, {it Herschel} and the Atacama Pathfinder EXperiment (APEX). We use the high-resolution {it HST}/WFC3 images to disentangle the background source from the foreground lens in {it Spitzer}/IRAC data. The detections and upper limits provide important constraints on the spectral energy distributions (SEDs) for these DSFGs, yielding stellar masses, IR luminosities, and star formation rates (SFRs). The SED fits of six SPT sources show that the intrinsic stellar masses span a range more than one order of magnitude with a median value $sim$ 5 $times 10^{10}M_{Sun}$. The intrinsic IR luminosities range from 4$times 10^{12}L_{Sun}$ to 4$times 10^{13}L_{Sun}$. They all have prodigious intrinsic star formation rates of 510 to 4800 $M_{Sun} {rm yr}^{-1}$. Compared to the star-forming main sequence (MS), these six DSFGs have specific SFRs that all lie above the MS, including two galaxies that are a factor of 10 higher than the MS. Our results suggest that we are witnessing the ongoing strong starburst events which may be driven by major mergers.
We present the public data release of halo and galaxy catalogues extracted from the EAGLE suite of cosmological hydrodynamical simulations of galaxy formation. These simulations were performed with an enhanced version of the GADGET code that includes a modified hydrodynamics solver, time-step limiter and subgrid treatments of baryonic physics, such as stellar mass loss, element-by-element radiative cooling, star formation and feedback from star formation and black hole accretion. The simulation suite includes runs performed in volumes ranging from 25 to 100 comoving megaparsecs per side, with numerical resolution chosen to marginally resolve the Jeans mass of the gas at the star formation threshold. The free parameters of the subgrid models for feedback are calibrated to the redshift z=0 galaxy stellar mass function, galaxy sizes and black hole mass - stellar mass relation. The simulations have been shown to match a wide range of observations for present-day and higher-redshift galaxies. The raw particle data have been used to link galaxies across redshifts by creating merger trees. The indexing of the tree produces a simple way to connect a galaxy at one redshift to its progenitors at higher redshift and to identify its descendants at lower redshift. In this paper we present a relational database which we are making available for general use. A large number of properties of haloes and galaxies and their merger trees are stored in the database, including stellar masses, star formation rates, metallicities, photometric measurements and mock gri images. Complex queries can be created to explore the evolution of more than 10^5 galaxies, examples of which are provided in appendix. (abridged)
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