No Arabic abstract
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.
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.
We present the results of a new search for galaxy-scale strong lensing systems in CFHTLS Wide. Our lens-finding technique involves a preselection of potential lens galaxies, applying simple cuts in size and magnitude. We then perform a Principal Component Analysis of the galaxy images, ensuring a clean removal of the light profile. Lensed features are searched for in the residual images using the clustering topometric algorithm DBSCAN. We find 1098 lens candidates that we inspect visually, leading to a cleaned sample of 109 new lens candidates. Using realistic image simulations we estimate the completeness of our sample and show that it is independent of source surface brightness, Einstein ring size (image separation) or lens redshift. We compare the properties of our sample to previous lens searches in CFHTLS. Including the present search, the total number of lenses found in CFHTLS amounts to 678, which corresponds to ~4 lenses per square degree down to i=24.8. This is equivalent to ~ 60.000 lenses in total in a survey as wide as Euclid, but at the CFHTLS resolution and depth.
We extend the halo-based group finder developed by Yang et al. (2005b) to use data {it simultaneously} with either photometric or spectroscopic redshifts. A mock galaxy redshift surveys constructed from a high-resolution N-body simulation is used to evaluate the performance of this extended group finder. For galaxies with magnitude ${rm zle 21}$ and redshift $0<zle 1.0$ in the DESI legacy imaging surveys (The Legacy Surveys), our group finder successfully identifies more than 60% of the members in about $90%$ of halos with mass $ga 10^{12.5}msunh$. Detected groups with mass $ga 10^{12.0}msunh$ have a purity (the fraction of true groups) greater than 90%. The halo mass assigned to each group has an uncertainty of about 0.2 dex at the high mass end $ga 10^{13.5}msunh$ and 0.45 dex at the low mass end. Groups with more than 10 members have a redshift accuracy of $sim 0.008$. We apply this group finder to the Legacy Surveys DR8 and find 6.4 Million groups with at least 3 members. About 500,000 of these groups have at least 10 members. The resulting catalog containing 3D coordinates, richness, halo masses, and total group luminosities, is made publicly available.
We present the data release of the Gemini-South GMOS spectroscopy in the fields of 11 galaxy groups at $0.8<z<1$, within the COSMOS field. This forms the basis of the Galaxy Environment Evolution Collaboration 2 (GEEC2) project to study galaxy evolution in haloes with $Msim 10^{13}M_odot$ across cosmic time. The final sample includes $162$ spectroscopically--confirmed members with $R<24.75$, and is $>50$ per cent complete for galaxies within the virial radius, and with stellar mass $M_{rm star}>10^{10.3}M_odot$. Including galaxies with photometric redshifts we have an effective sample size of $sim 400$ galaxies within the virial radii of these groups. We present group velocity dispersions, dynamical and stellar masses. Combining with the GCLASS sample of more massive clusters at the same redshift we find the total stellar mass is strongly correlated with the dynamical mass, with $log{M_{200}}=1.20left(log{M_{rm star}}-12right)+14.07$. This stellar fraction of $~sim 1$ per cent is lower than predicted by some halo occupation distribution models, though the weak dependence on halo mass is in good agreement. Most groups have an easily identifiable most massive galaxy (MMG) near the centre of the galaxy distribution, and we present the spectroscopic properties and surface brightness fits to these galaxies. The total stellar mass distribution in the groups, excluding the MMG, compares well with an NFW profile with concentration $4$, for galaxies beyond $sim 0.2R_{200}$. This is more concentrated than the number density distribution, demonstrating that there is some mass segregation.
We present a semi-analytic model of satellite galaxies, SatGen, which can generate large samples of satellite populations for a host halo of desired mass, redshift, and assembly history. The model combines dark-matter halo merger trees, empirical relations for the galaxy-halo connection, and analytic prescriptions for tidal effects, dynamical friction, and ram pressure stripping. SatGen emulates cosmological zoom-in hydro-simulations in certain aspects. Satellites can reside in cored or cuspy DM subhaloes, depending on the halo response to baryonic physics that can be formulated from hydro-simulations and physical modeling. The subhalo profile and the stellar mass and size of a satellite evolves depending on its tidal mass loss and initial structure. The host galaxy can include a baryonic disc and a stellar bulge, each described by a density profile that allows analytic orbit integration. SatGen complements simulations by propagating the effect of halo response found in simulated field galaxies to satellites (not properly resolved in simulations) and outperforms simulations by sampling the halo-to-halo variance of satellite statistics and overcoming artificial disruption due to insufficient resolution. As a first application, we use the model to study satellites of Milky Way sized hosts, making it emulate simulations of bursty star formation and of smooth star formation, respectively, and to experiment with a disc potential in the host halo. Our model reproduces the observed satellite statistics reasonably well. Different physical recipes make a difference in satellite abundance and spatial distribution at the 25% level, not large enough to be distinguished by current observations given the halo-to-halo variance. The MW disc depletes satellites by 20% and has a subtle effect of diversifying the internal structure of satellites, important for alleviating certain small-scale problems.