No Arabic abstract
The number density and correlation function of galaxies are two key quantities to characterize the distribution of the observed galaxy population. High-$z$ spectroscopic surveys, which usually involve complex target selection and are incomplete in redshift sampling, present both opportunities and challenges to measure these quantities reliably in the high-$z$ Universe. Using realistic mock catalogs we show that target selection and redshift incompleteness can lead to significantly biased results. We develop methods to correct such bias, using information provided by the parent photometric data from which the spectroscopic sample is constructed. Our tests using realistic mock samples show that our methods are able to reproduce the true stellar mass function and correlation function reliably. As applications, mock catalogs are constructed for two high-z surveys: the existing zCOSMOS-bright galaxy sample and the forthcoming PFS galaxy evolution survey. We apply our methods to the zCOSMOS-bright sample and make comparisons with results obtained before. The same set of mock samples are used to quantify cosmic variances expected for different sample sizes. We find that, for both number density and correlation function, the relative error due to cosmic variance in the PFS galaxy survey will be reduced by a factor of 3-4 when compared to zCOSMOS.
Identifying galaxy groups from redshift surveys of galaxies plays an important role in connecting galaxies with the underlying dark matter distribution. Current and future high-$z$ spectroscopic surveys, usually incomplete in redshift sampling, present both opportunities and challenges to identifying groups in the high-$z$ Universe. We develop a group finder that is based on incomplete redshift samples combined with photometric data, using a machine learning method to assign halo masses to identified groups. Test using realistic mock catalogs shows that $gtrsim 90%$ of true groups with halo masses $rm M_h gtrsim 10^{12} M_{odot}/h$ are successfully identified, and that the fraction of contaminants is smaller than $10%$. The standard deviation in the halo mass estimation is smaller than 0.25 dex at all masses. We apply our group finder to zCOSMOS-bright and describe basic properties of the group catalog obtained.
We develop empirical methods for modeling the galaxy population and populating cosmological N-body simulations with mock galaxies according to the observed properties of galaxies in survey data. We use these techniques to produce a new set of mock catalogs for the DEEP2 Galaxy Redshift Survey based on the output of the high-resolution Bolshoi simulation, as well as two other simulations with different cosmological parameters, all of which we release for public use. The mock-catalog creation technique uses subhalo abundance matching to assign galaxy luminosities to simulated dark-matter halos. It then adds color information to the resulting mock galaxies in a manner that depends on the local galaxy density, in order to reproduce the measured color-environment relation in the data. In the course of constructing the catalogs, we test various models for including scatter in the relation between halo mass and galaxy luminosity, within the abundance-matching framework. We find that there is no constant-scatter model that can simultaneously reproduce both the luminosity function and the autocorrelation function of DEEP2. This result has implications for galaxy-formation theory, and it restricts the range of contexts in which the mocks can be usefully applied. Nevertheless, careful comparisons show that our new mocks accurately reproduce a wide range of the other properties of the DEEP2 catalog, suggesting that they can be used to gain a detailed understanding of various selection effects in DEEP2.
We present a new suite of mock galaxy catalogs mimicking the low-redshift Universe, based on an updated halo occupation distribution (HOD) model and a scaling relation between optical properties and the neutral hydrogen (HI) content of galaxies. Our algorithm is constrained by observations of the luminosity function and luminosity- and colour-dependent clustering of SDSS galaxies, as well as the HI mass function and HI-dependent clustering of massive HI-selected galaxies in the ALFALFA survey. Mock central and satellite galaxies with realistic values of $r$-band luminosity, $g-r$ and $u-r$ colour, stellar mass and HI mass are populated in an $N$-body simulation, inheriting a number of properties of the density and tidal environment of their host halos. The host halo of each central galaxy is also `baryonified with realistic spatial distributions of stars as well as hot and cold gas, along with the corresponding rotation curve. Our default HOD assumes that galaxy properties are a function of group halo mass alone, and can optionally include effects such as galactic conformity and colour-dependent galaxy assembly bias. The mocks predict the relation between the stellar mass and HI mass of massive HI galaxies, as well as the 2-point cross-correlation function of spatially co-located optical and HI-selected samples. They enable novel null tests for galaxy assembly bias, provide predictions for the HI velocity width function, and clarify the origin and universality of the radial acceleration relation in the $Lambda$CDM framework.
We study the topology of the matter density field in two dimensional slices, and consider how we can use the amplitude $A$ of the genus for cosmological parameter estimation. Using the latest Horizon Run 4 simulation data, we calculate the genus of the smoothed density field constructed from lightcone mock galaxy catalogs. Information can be extracted from the amplitude of the genus by considering both its redshift evolution and magnitude. The constancy of the genus amplitude with redshift can be used as a standard population, from which we derive constraints on the equation of state of dark energy $w_{rm de}$ - by measuring $A$ at $z sim 0.1$ and $z sim 1$, we can place an order $Delta w_{rm de} sim {cal O}(15%)$ constraint on $w_{rm de}$. By comparing $A$ to its Gaussian expectation value we can potentially derive an additional stringent constraint on the matter density $Delta Omega_{rm mat} sim 0.01$. We discuss the primary sources of contamination associated with the two measurements - redshift space distortion and shot noise. With accurate knowledge of galaxy bias, we can successfully remove the effect of redshift space distortion, and the combined effect of shot noise and non-linear gravitational evolution is suppressed by smoothing over suitably large scales $R_{rm G} ge 15 {rm Mpc}/h$. Without knowledge of the bias, we discuss how joint measurements of the two and three dimensional genus can be used to constrain the growth factor $beta = f/b$. The method can be applied optimally to redshift slices of a galaxy distribution generated using the drop-off technique.
Halo Occupation Distribution (HOD) is a model giving the average number of galaxies in a dark matter halo, function of its mass and other intrinsic properties, like distance from halo center, luminosity and redshift of its constituting galaxies. It is believed that these parameters could also be related to the galaxy history of formation. We want to investigate more this relation in order to test and better refine this model. To do that, we extract HOD indicators from EUCLID mock catalogs for different luminosity cuts and for redshifts ranges going from 0.1 < z < 3.0. We study and interpret the trends of indicators function of these variations and tried to retrace galaxy formation history following the idea that galaxy evolution is the combination rather than the conflict of the two main proposed ideas nowadays: the older hierarchical mass merger driven paradigm and the recent downsizing star formation driven approach.