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Register a new userNumerical Galaxy Catalog -I. A Semi-analytic Model of Galaxy Formation with N-body simulations
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We construct the Numerical Galaxy Catalog ($ u$GC), based on a semi-analytic model of galaxy formation combined with high-resolution N-body simulations in a $Lambda$-dominated flat cold dark matter ($Lambda$CDM) cosmological model. The model includes several essential ingredients for galaxy formation, such as merging histories of dark halos directly taken from N-body simulations, radiative gas cooling, star formation, heating by supernova explosions (supernova feedback), mergers of galaxies, population synthesis, and extinction by internal dust and intervening HI clouds. As the first paper in a series using this model, we focus on basic photometric, structural and kinematical properties of galaxies at present and high redshifts. Two sets of model parameters are examined, strong and weak supernova feedback models, which are in good agreement with observational luminosity functions of local galaxies in a range of observational uncertainty. Both models agree well with many observations such as cold gas mass-to-stellar luminosity ratios of spiral galaxies, HI mass functions, galaxy sizes, faint galaxy number counts and photometric redshift distributions in optical pass-bands, isophotal angular sizes, and cosmic star formation rates. In particular, the strong supernova feedback model is in much better agreement with near-infrared (K-band) faint galaxy number counts and redshift distribution than the weak feedback model and our previous semi-analytic models based on the extended Press-Schechter formalism. (Abridged)
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This is the first paper of a series that describes the methods and basic results of the GalICS model (for Galaxies In Cosmological Simulations). GalICS is a hybrid model for hierarchical galaxy formation studies, combining the outputs of large cosmological N-body simulations with simple, semi-analytic recipes to describe the fate of the baryons within dark matter halos. The simulations produce a detailed merging tree for the dark matter halos including complete knowledge of the statistical properties arising from the gravitational forces. We intend to predict the overall statistical properties of galaxies, with special emphasis on the panchromatic spectral energy distribution emitted by galaxies in the UV/optical and IR/submm wavelength ranges. In this paper, we outline the physically motivated assumptions and key free parameters that go into the model, comparing and contrasting with other parallel efforts. We specifically illustrate the success of the model in comparison to several datasets, showing how it is able to predict the galaxy disc sizes, colours, luminosity functions from the ultraviolet to far infrared, the Tully--Fisher and Faber--Jackson relations, and the fundamental plane in the local universe. We also identify certain areas where the model fails, or where the assumptions needed to succeed are at odds with observations, and pay special attention to understanding the effects of the finite resolution of the simulations on the predictions made. Other papers in this series will take advantage of different data sets available in the literature to extend the study of the limitations and predictive power of GalICS, with particular emphasis put on high-redshift galaxies.
We present a new cosmological galaxy formation model, $ u^2$GC, as an updated version of our previous model $ u$GC. We adopt the so-called semi-analytic approach, in which the formation history of dark matter halos is computed by ${it N}$-body simulations, while the baryon physics such as gas cooling, star formation and supernova feedback are simply modeled by phenomenological equations. Major updates of the model are as follows: (1) the merger trees of dark matter halos are constructed in state-of-the-art ${it N}$-body simulations, (2) we introduce the formation and evolution process of supermassive black holes and the suppression of gas cooling due to active galactic nucleus (AGN) activity, (3) we include heating of the intergalactic gas by the cosmic UV background, and (4) we tune some free parameters related to the astrophysical processes using a Markov chain Monte Carlo method. Our ${it N}$-body simulations of dark matter halos have unprecedented box size and mass resolution (the largest simulation contains 550 billion particles in a 1.12 Gpc/h box), enabling the study of much smaller and rarer objects. The model was tuned to fit the luminosity functions of local galaxies and mass function of neutral hydrogen. Local observations, such as the Tully-Fisher relation, size-magnitude relation of spiral galaxies and scaling relation between the bulge mass and black hole mass were well reproduced by the model. Moreover, the model also well reproduced the cosmic star formation history and the redshift evolution of rest-frame ${it K}$-band luminosity functions. The numerical catalog of the simulated galaxies and AGNs is publicly available on the web.
We generate mock galaxy catalogues for a grid of different cosmologies, using rescaled N-body simulations in tandem with a semi-analytic model run using consistent parameters. Because we predict the galaxy bias, rather than fitting it as a nuisance parameter, we obtain an almost pure constraint on sigma_8 by comparing the projected two-point correlation function we obtain to that from the SDSS. A systematic error arises because different semi-analytic modelling assumptions allow us to fit the r-band luminosity function equally well. Combining our estimate of the error from this source with the statistical error, we find sigma_8=0.97 +/- 0.06. We obtain consistent results if we use galaxy samples with a different magnitude threshold, or if we select galaxies by b_J-band rather than r-band luminosity and compare to data from the 2dFGRS. Our estimate for sigma_8 is higher than that obtained for other analyses of galaxy data alone, and we attempt to find the source of this difference. We note that in any case, galaxy clustering data provide a very stringent constraint on galaxy formation models.
It is now possible for hydrodynamical simulations to reproduce a representative galaxy population. Accordingly, it is timely to assess critically some of the assumptions of traditional semi-analytic galaxy formation models. We use the Eagle simulations to assess assumptions built into the Galform semi-analytic model, focussing on those relating to baryon cycling, angular momentum and feedback. We show that the assumption in Galform that newly formed stars have the same specific angular momentum as the total disc leads to a significant overestimate of the total stellar specific angular momentum of disc galaxies. In Eagle, stars form preferentially out of low specific angular momentum gas in the interstellar medium (ISM) due to the assumed gas density threshold for stars to form, leading to more realistic galaxy sizes. We find that stellar mass assembly is similar between Galform and Eagle but that the evolution of gas properties is different, with various indications that the rate of baryon cycling in Eagle is slower than is assumed in Galform. Finally, by matching individual galaxies between Eagle and Galform, we find that an artificial dependence of AGN feedback and gas infall rates on halo mass doubling events in Galform drives most of the scatter in stellar mass between individual objects. Put together our results suggest that the Galform semi-analytic model can be significantly improved in light of recent advances.
We present hydrodynamical N-body simulations of clusters of galaxies with feedback taken from semi-analytic models of galaxy formation. The advantage of this technique is that the source of feedback in our simulations is a population of galaxies that closely resembles that found in the real universe. We demonstrate that, to achieve the high entropy levels found in clusters, active galactic nuclei must inject a large fraction of their energy into the intergalactic/intracluster media throughout the growth period of the central black hole. These simulations reinforce the argument of Bower et al. (2008), who arrived at the same conclusion on the basis of purely semi-analytic reasoning.
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