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Register a new userGalaxy Evolution in Cosmological Simulations With Outflows I: Stellar Masses and Star Formation Rates
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Romeel Dave
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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.
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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.
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 use cosmological hydrodynamic simulations to investigate how inflows, star formation, and outflows govern the the gaseous and metal content of galaxies. In our simulations, galaxy metallicities are established by a balance between inflows and outflows as governed by the mass outflow rate, implying that the mass-metallicity relation reflects how the outflow rate varies with stellar mass (M*). Gas content is set by a competition between inflow into and gas consumption within the ISM, the latter being governed by the SF law, while the former is impacted by both wind recycling and preventive feedback. Stochastic variations in the inflow rate move galaxies off the equilibrium M*-Z and Z*-fgas relations in a manner correlated with star formation rate, and the scatter is set by the timescale to re-equilibrate. The evolution of both relations from z=3-0 is slow, as individual galaxies tend to evolve mostly along the relations. Gas fractions at a given M* slowly decrease with time because the cosmic inflow rate diminishes faster than the consumption rate, while metallicities slowly increase as infalling gas becomes more enriched. Observations from z~3-0 are better matched by simulations employing momentum-driven wind scalings rather than constant wind speeds, but all models predict too low gas fractions at low masses and too high metallicities at high M*. All our models reproduce observed second-parameter trends of the mass-metallicity relation with star formation rate and environment, indicating that these are a consequence of equilibrium and not feedback. Overall, the analytical framework of our equilibrium scenario broadly captures the relevant physics establishing the galaxy gas and metal content in simulations, which suggests that the cycle of baryonic inflows and outflows centrally governs the cosmic evolution of these properties in typical star-forming galaxies.
Establishing the stellar masses (M*), and hence specific star-formation rates (sSFRs) of submillimetre galaxies (SMGs) is crucial for determining their role in the cosmic galaxy/star formation. However, there is as yet no consensus over the typical M* of SMGs. Specifically, even for the same set of SMGs, the reported average M* have ranged over an order of magnitude, from ~5x10^10 Mo to ~5x10^11 Mo. Here we study how different methods of analysis can lead to such widely varying results. We find that, contrary to recent claims in the literature, potential contamination of IRAC 3-8 um photometry from hot dust associated with an active nucleus is not the origin of the published discrepancies in derived M*. Instead, we expose in detail how inferred M* depends on assumptions made in the photometric fitting, and quantify the individual and cumulative effects of different choices of initial mass function, different brands of evolutionary synthesis models, and different forms of assumed star-formation history. We review current observational evidence for and against these alternatives as well as clues from the hydrodynamical simulations, and conclude that, for the most justifiable choices of these model inputs, the average M* of SMGs is ~2x10^11 Mo. We also confirm that this number is perfectly reasonable in the light of the latest measurements of their dynamical masses, and the evolving M* function of the overall galaxy population. M* of this order imply that the average sSFR of SMGs is comparable to that of other star-forming galaxies at z>2, at 2-3 Gyr^-1. This supports the view that, while rare outliers may be found at any M*, most SMGs simply form the top end of the main-sequence of star-forming galaxies at these redshifts. Conversely, this argues strongly against the viewpoint that SMGs are extreme pathological objects, of little relevance in the cosmic history of star-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.
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