Search

We use a large K-selected sample of 299,961 galaxies from the REFINE survey, consisting of a combination of data from three of the deepest near-infrared surveys: UKIDSS UDS, COSMOS/UltraVISTA and CFHTLS-D1/VIDEO, that were homogeneously reduced to obtain photometric redshifts and stellar masses. We detect 2588 candidate galaxy groups up to $z=3.15$ at $S/N>1.5$. We build a very pure ($>90\%$) sample of 448 candidate groups up to $z=2.5$ and study some of their properties. Cluster detection is done using the DElaunay TEssellation ClusTer IdentiFication with photo-z (DETECTIFz) algorithm that we describe. This new group finder algorithm uses the joint probability distribution functions (PDF) of redshift and stellar-mass of galaxies to detect groups as stellar-mass overdensities in overlapping redshift slices, where density is traced using Monte Carlo realisation of the Delaunay Tessellation Field Estimator (DTFE). We compute the algorithm selection function using mock galaxy catalogues taken from cosmological N-body simulation lightcones. Based on these simulations, we reach a completeness of $\sim80\%$ for clusters ($M_{200}>10^{14} M_{\odot}$) at a purity of $\sim90\%$ at $z, Comment: Accepted in MNRAS. 21 pages (18 + 3 in appendix). 9 figures. Include online only appendix of the published version

Obtaining large samples of galaxy groups and (proto-)cluster cores at redshift z > 1.5 is crucial to better understand cluster formation and the role environment plays in shaping galaxy properties. While dozens of these structures have now been studied, a systematic search for such systems has proven challenging. Exploiting deep near-infrared selected photometric data is a promising approach. We designed a new group finder algorithm, the DElaunay TEssellation ClusTer IdentiFication with photo-z (DETECTIFz) to detect galaxy groups in photometric data. The algorithm uses the joint PDF of redshift and stellar mass of galaxies to identify groups as stellar-mass over-densities. Using data from three of the deepest near-infrared surveys: UKIDSS UDS, VIDEO, and UltraVISTA, that were homogeneously reduced (the REFINE survey), we build a pure (>90%) sample of 448 candidate groups up to z=2.5 and study some of their properties. In this talk, I present results from Sarron & Conselice (accepted in MNRAS). I will detail the DETECTIFz algorithm and show its performances on mock galaxy catalogues. I will show some properties of our group catalogue. In particular, we find that galaxies with \(10.25 < \log(M_\star/{\rm M}_\odot) < 11\) have higher quenched fractions in groups than in the field up to z=2.2, the difference growing with decreasing redshift., This work was supported by a Cosmic Visions STFC grant

Upcoming wide-field surveys are well-suited to studying the growth of galaxy clusters by tracing galaxy and gas accretion along cosmic filaments. We use hydrodynamic simulations of volumes surrounding 324 clusters from The ThreeHundred project to develop a framework for identifying and characterising these filamentary structures, and associating galaxies with them. We define 3-dimensional reference filament networks reaching 5R200 based on the underlying gas distribution and quantify their recovery using mock galaxy samples mimicking observations such as those of the WEAVE Wide-Field Cluster Survey. Since massive galaxies trace filaments, they are best recovered by mass-weighting galaxies or imposing a bright limit (e.g. > L ∗ ) on their selection. We measure the transverse gas density profile of filaments, derive a characteristic filament radius of ' 0.7–1 h −1Mpc, and use this to assign galaxies to filaments. For different filament extraction methods we find that at R > R200, ∼ 15–20% of galaxies with M∗ > 3 × 109M are in filaments, increasing to ∼ 60% for galaxies more massive than the Milky-Way. The fraction of galaxies in filaments is independent of cluster mass and dynamical state, and is a function of cluster-centric distance, increasing from ∼ 13% at 5R200 to ∼ 21% at 1.5R200. As a bridge to the design of observational studies, we measure the purity and completeness of different filament galaxy selection strategies. Encouragingly, the overall 3-dimensional filament networks and ∼ 67% of the galaxies associated with them are recovered from 2-dimensional galaxy positions.

Poster presented at the conference Galaxy evolution Across Time, 12-16 June, Paris, France There is some disagreement in the literature concerning the evolution with redshift of the galaxy luminosity function (GLF) in galaxy clusters. Indeed, it is still unclear whether the red sequence (RS) is enriched by efficient quenching of blue late-type galaxies inside the cluster from z of about 1, or if this RS is built at higher redshift. Solving this contradiction is important to understand the physical processes driving the quenching of galaxies. However, the study of the GLF evolution has been limited to small samples and these different conclusions could be due to cluster to cluster variations. To explore this possibility, we applied our new version of the Adami and MAzure Cluster FInder (AMACFI) to the Canada France Hawaii Telescope Legacy Survey (CFHTLS) W1 field. We thus built a catalogue of thousands of cluster candidates up to z of about 1. We present the selection function of our detection algorithm. We study the evolution of the galaxy luminosity function of galaxy clusters with both redshift and cluster mass, and show preliminary results. Taking advantage of our large sample of clusters, we shall be able to break the degeneracy between redshift and mass dependence in the near future.