Related papers: A Probabilistic Quantification of Galaxy Cluster M…
In order to study the galaxy population of galaxy clusters with photometric data one must be able to accurately discriminate between cluster members and non-members. The redMaPPer cluster finding algorithm treats this problem…
We introduce a new effective strategy to assign group and cluster membership probabilities $P_{mem}$ to galaxies using photometric redshift information. Large dynamical ranges both in halo mass and cosmic time are considered. The method…
The studies of the evolution of galaxies in Galaxy Clusters have as a traditional complication the difficulty in establishing cluster membership of those sources detected in the field of view. The determination of spectroscopic redshifts…
Numerous methods for finding clusters at moderate to high redshifts have been proposed in recent years, at wavelengths ranging from radio to X-rays. In this paper we describe a new method for detecting clusters in two-band optical/near-IR…
We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive…
Clusters of galaxies in most previous catalogs have redshifts z<0.3. Using the photometric redshifts of galaxies from the Sloan Digital Sky Survey Data Release 6 (SDSS DR6), we identify 39,668 clusters in the redshift range 0.05< z <0.6…
We present the first results of our application of photometric redshifts to the study of galaxy populations in high-redshift clusters. For this survey, we are examining a sample of galaxy clusters at z > 0.6 which have already been…
The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties, galaxy cluster abundances and therefore, constraining cosmological parameters. We present a new technique for…
Wide-field optical imaging surveys are efficient at identifying galaxy clusters, but optically identified clusters suffer from projection effects--physically unassociated galaxies along the line of sight can be misidentified as cluster…
We develop a galaxy cluster finding algorithm based on spectral clustering technique to identify optical counterparts and estimate optical redshifts for X-ray selected cluster candidates. As an application, we run our algorithm on a sample…
The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M200>=1E14 Msun/h extracted from a…
The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties or galaxy cluster abundances and therefore, constraining cosmological parameters. We present a new technique for…
We present the clustering of galaxy clusters as a useful addition to the common set of cosmological observables. The clustering of clusters probes the large-scale structure of the Universe, extending galaxy clustering analysis to the…
We present a new method for photometering objects in galaxy clusters. We introduce a mode-filtering technique for removing spatially variable backgrounds, improving both detection and photometric accuracy (roughly halving the scatter in the…
We investigate, using simulated galaxy catalogues, the completeness of searches for massive clusters of galaxies in redshift surveys or imaging surveys with photometric redshift estimates, i.e. what fraction of clusters (M>10^14/h Msun) are…
We present a new cluster detection algorithm designed for finding high-redshift clusters using optical/infrared imaging data. The algorithm has two main characteristics. First, it utilises each galaxy's full redshift probability function,…
We compile a sample of spectroscopically- and photometrically-selected cluster galaxies from four high-redshift galaxy clusters ($1.59 < z < 1.71$) from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS), and a comparison…
The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…
We describe an objective and automated method for detecting clusters of galaxies from optical imaging data. This method is a variant of the so-called `matched-filter' technique pioneered by Postman et al. (1996). With simultaneous use of…
We present a description of the observations and data reduction procedures for an extensive spectroscopic and multi-band photometric study of nine high redshift, optically-selected cluster candidates. The primary goal of the survey is to…