Abstract:
The anisotropy of clustering in redshift space provides a direct measure of the growth rate of large scale structure in the Universe. Future galaxy redshift surveys will make high precision measurements of these distortions, and will potentially allow us to distinguish between different scenarios for the accelerating expansion of the Universe. Accurate predictions are needed in order to distinguish between competing cosmological models. We study the distortions in the redshift space power spectrum in $\Lambda$CDM and quintessence dark energy models, using large volume N-body simulations, and test predictions for the form of the redshift space distortions. We find that the linear perturbation theory prediction by Kaiser (1987) is a poor fit to the measured distortions, even on surprisingly large scales $k \ge 0.05 h$Mpc$^{-1}$. An improved model for the redshift space power spectrum, including the non-linear velocity divergence power spectrum, is presented and agrees with the power spectra measured from the simulations up to $k \sim 0.2 h$Mpc$^{-1}$. We have found a density-velocity relation which is cosmology independent and which relates the non-linear velocity divergence spectrum to the non-linear matter power spectrum. We provide a formula which generates the non-linear velocity divergence $P(k)$ at any redshift, using only the non-linear matter power spectrum and the linear growth factor at the desired redshift. This formula is accurate to better than 5% on scales $k<0.2 h $Mpc$^{-1}$ for all the cosmological models discussed in this paper. Our results will extend the statistical power of future galaxy surveys.

Abstract:
The non-linear, scale-dependent bias in the mass distribution of galaxies and the underlying dark matter is a key systematic affecting the extraction of cosmological parameters from galaxy clustering. Using 95 million halos from the Millennium-XXL N-body simulation, we find that the mass bias is scale independent only for $k<0.1 h{\rm Mpc}^{-1}$ today ($z=0$) and for $k<0.2 h{\rm Mpc}^{-1}$ at $z=0.7$. We test analytic halo bias models against our simulation measurements and find that the model of Tinker et al. 2005 is accurate to better then 5% at $z=0$. However, the simulation results are better fit by an ellipsoidal collapse model at $z=0.7$. We highlight, for the first time, another potentially serious systematic due to a sampling bias in the halo velocity divergence power spectra which will affect the comparison between observations and any redshift space distortion model which assumes dark matter velocity statistics with no velocity bias. By measuring the velocity divergence power spectra for different sized halo samples, we find that there is a significant bias which increases with decreasing number density. This bias is approximately 20% at $k=0.1h$Mpc$^{-1}$ for a halo sample of number density $\bar{n} = 10^{-3} (h/$Mpc$)^3$ at both $z=0$ and $z=0.7$ for the velocity divergence auto power spectrum. Given the importance of redshift space distortions as a probe of dark energy and the on-going major effort to advance models for the clustering signal in redshift space, our results show this velocity bias introduces another systematic, alongside scale-dependent halo mass bias, which cannot be neglected.

Abstract:
Future galaxy surveys hope to distinguish between the dark energy and modified gravity scenarios for the accelerating expansion of the Universe using the distortion of clustering in redshift space. The aim is to model the form and size of the distortion to infer the rate at which large scale structure grows. We test this hypothesis and assess the performance of current theoretical models for the redshift space distortion using large volume N-body simulations of the gravitational instability process. We simulate competing cosmological models which have identical expansion histories - one is a quintessence dark energy model with a scalar field and the other is a modified gravity model with a time varying gravitational constant - and demonstrate that they do indeed produce different redshift space distortions. This is the first time this approach has been verified using a technique that can follow the growth of structure at the required level of accuracy. Our comparisons show that theoretical models for the redshift space distortion based on linear perturbation theory give a surprisingly poor description of the simulation results. Furthermore, the application of such models can give rise to catastrophic systematic errors leading to incorrect interpretation of the observations. We show that an improved model is able to extract the correct growth rate. Further enhancements to theoretical models of redshift space distortions, calibrated against simulations, are needed to fully exploit the forthcoming high precision clustering measurements.

Abstract:
We test an analytic model for the two-point correlations of galaxy clusters in redshift space using the Hubble Volume N-body simulations. The correlation function of clusters shows no enhancement along the line of sight, due to the lack of any virialised structures in the cluster distribution. However, the distortion of the clustering pattern due to coherent bulk motions is clearly visible. The distribution of cluster peculiar motions is well described by a Gaussian, except in the extreme high velocity tails. The simulations produce a small but significant number of clusters with large peculiar motions. The form of the redshift space power spectrum is strongly influenced by errors in measured cluster redshifts in extant surveys. When these errors are taken into account, the model reproduces the power spectrum recovered from the simulation to an accuracy of 15% or better over a decade in wavenumber. We compare our analytic predictions with the power spectrum measured from t! he! APM cluster redshift survey. The cluster power spectrum constrains the amplitude of density fluctuations, as measured by the linear rms variance in spheres of radius 8 h^(-1) Mpc, denoted by sigma_8. When combined with the constraints on sigma_8 and the density parameter Omega derived from the local abundance of clusters, we find a best fitting cold dark matter model with sigma_8~1.25 and Omega~0.2, for a power spectrum shape that matches that measured for galaxies. However, for the best fitting value of Omega and given the value of Hubble's constant from recent measurements, the assumed shape of the power spectrum is incompatible with the most readily motivated predictions from the cold dark matter paradigm.

Abstract:
We study the nonlinear growth of cosmic structure in different dark energy models, using large volume N-body simulations. We consider a range of quintessence models which feature both rapidly and slowly varying dark energy equations of state, and compare the growth of structure to that in a universe with a cosmological constant. The adoption of a quintessence model changes the expansion history of the universe, the form of the linear theory power spectrum and can alter key observables, such as the horizon scale and the distance to last scattering. We incorporate these effects into our simulations in stages to isolate the impact of each on the growth of structure. The difference in structure formation can be explained to first order by the difference in growth factor at a given epoch; this scaling also accounts for the nonlinear growth at the 15% level. We find that quintessence models that are different from $\Lambda$CDM both today and at high redshifts $(z \sim 1000)$ and which feature late $(z<2)$, rapid transitions in the equation of state, can have identical baryonic acoustic oscillation (BAO) peak positions to those in $\Lambda$CDM. We find that these models have higher abundances of dark matter haloes at $z>0$ compared to $\Lambda$CDM and so measurements of the mass function should allow us to distinguish these quintessence models from a cosmological constant. However, we find that a second class of quintessence models, whose equation of state makes an early $(z>2)$ rapid transition to $w=-1$, cannot be distinguished from $\Lambda$CDM using measurements of the mass function or the BAO, even if these models have non-negligible amounts of dark energy at early times.

Abstract:
For galaxy clustering to provide robust constraints on cosmological parameters and galaxy formation models, it is essential to make reliable estimates of the errors on clustering measurements. We present a new technique, based on a spatial Jackknife (JK) resampling, which provides an objective way to estimate errors on clustering statistics. Our approach allows us to set the appropriate size for the Jackknife subsamples. The method also provides a means to assess the impact of individual regions on the measured clustering, and thereby to establish whether or not a given galaxy catalogue is dominated by one or several large structures, preventing it to be considered as a "fair sample". We apply this methodology to the two- and three-point correlation functions measured from a volume limited sample of M* galaxies drawn from data release seven of the Sloan Digital Sky Survey (SDSS). The frequency of jackknife subsample outliers in the data is shown to be consistent with that seen in large N-body simulations of clustering in the cosmological constant plus cold dark matter cosmology. We also present a comparison of the three-point correlation function in SDSS and 2dFGRS using this approach and find consistent measurements between the two samples.

Abstract:
We present a dynamical model of supernova feedback which follows the evolution of pressurised bubbles driven by supernovae in a multi-phase interstellar medium (ISM). The bubbles are followed until the point of break-out into the halo, starting from an initial adiabatic phase to a radiative phase. We show that a key property which sets the fate of bubbles in the ISM is the gas surface density, through the work done by the expansion of bubbles and its role in setting the gas scaleheight. The multi-phase description of the ISM is essential, and neglecting it leads to order of magnitude differences in the predicted outflow rates. We compare our predicted mass loading and outflow velocities to observations of local and high-redshift galaxies and find good agreement over a wide range of stellar masses and velocities. With the aim of analysing the dependence of the mass loading of the outflow, beta (i.e. the ratio between the outflow and star formation rates), on galaxy properties, we embed our model in the galaxy formation simulation, GALFORM, set in the LCDM framework. We find that a dependence of beta solely on the circular velocity, as is widely assumed in the literature, is actually a poor description of the outflow rate, as large variations with redshift and galaxy properties are obtained. Moreover, we find that below a circular velocity of 80km/s the mass loading saturates. A more fundamental relation is that between beta and the gas scaleheight of the disk, hg, and the gas fraction, fgas, as beta hg^(1.1) fgas^(0.4), or the gas surface density, \Sigma_g, and the gas fraction, as beta \Sigma_g^(-0.6) fgas^(0.8). We find that using the new mass loading model leads to a shallower faint-end slope in the predicted optical and near-IR galaxy luminosity functions.

Abstract:
We study the properties of Ly-alpha emitters in a cosmological framework by computing the escape of Ly-alpha photons through galactic outflows. We combine the GALFORM semi-analytical model of galaxy formation with a Monte Carlo Ly-alpha radiative transfer code. The properties of Ly-alpha emitters at 0

Abstract:
The latest observations of molecular gas and the atomic hydrogen content of local and high-redshift galaxies, coupled with how these correlate with star formation activity, have revolutionized our ideas about how to model star formation in a galactic context. A successful theory of galaxy formation has to explain some key facts: (i) high-redshift galaxies have higher molecular gas fractions and star formation rates than local galaxies, (ii) scaling relations show that the atomic-to-stellar mass ratio decreases with stellar mass in the local Universe, and (iii) the global abundance of atomic hydrogen evolves very weakly with time. We review how modern cosmological simulations of galaxy formation attempt to put these pieces together and highlight how approaches simultaneously solving dark matter and gas physics, and approaches first solving the dark matter N-body problem and then dealing with gas physics using semi-analytic models, differ and complement each other. We review the observable predictions, what we think we have learned so far and what still needs to be done in the simulations to allow robust testing by the new observations expected from telescopes such as ALMA, PdBI, LMT, JVLA, ASKAP, MeerKAT, SKA.

Abstract:
The observed ultraviolet continuum (UVC) slope is potentially a powerful diagnostic of dust obscuration in star forming galaxies. However, the intrinsic slope is also sensitive to the form of the stellar initial mass function (IMF) and to the recent star formation and metal enrichment histories of a galaxy. Using the galform semi-analytical model of galaxy formation, we investigate the intrinsic distribution of UVC slopes. For star-forming galaxies, we find that the intrinsic distribution of UVC slopes at z=0, parameterised by the power law index beta, has a standard deviation of sigma_beta=0.30. This suggests an uncertainty on the inferred UV attenuation of A_fuv=0.7$ (assuming a Calzetti attenuation curve) for an individual object, even with perfect photometry. Furthermore, we find that the intrinsic UVC slope correlates with star formation rate, intrinsic UV luminosity, stellar mass and redshift. These correlations have implications for the interpretation of trends in the observed UVC slope with these quantities irrespective of the sample size or quality of the photometry. Our results suggest that in some cases the attenuation by dust has been incorrectly estimated.