A GMBCG Galaxy Cluster Catalog of 55,424 Rich Clusters from SDSS DR7 (original) (raw)
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A GMBCG Galaxy Cluster Catalog of 55,437 Rich Clusters from SDSS DR7
2011
We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plus Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy clusters and does not exist among field galaxies. Red sequence clustering in color space is detected using an Error Corrected Gaussian Mixture Model. We run GMBCG on 8240 square degrees of photometric data from SDSS DR7 to assemble the largest ever optical galaxy cluster catalog, consisting of over 55,000 rich clusters across the redshift range from 0.1 < z < 0.55. We present Monte Carlo tests of completeness and purity and perform cross-matching with X-ray clusters and with the maxBCG sample at low redshift. These tests indicate high completeness and purity across the full redshift range for clusters with 15 or more members.
MaxBCG: A red-sequence galaxy cluster finder
The Astrophysical …, 2007
Measurements of galaxy cluster abundances, clustering properties, and massto-light ratios in current and future surveys can provide important cosmological constraints. Digital wide-field imaging surveys, the recently-demonstrated fidelity of red-sequence cluster detection techniques, and a new generation of realistic mock galaxy surveys provide the means for construction of large, cosmologically-interesting cluster samples, whose selection and properties can be understood in unprecedented depth. We present the details of the "maxBCG" algorithm, a cluster-detection technique tailored to multi-band CCD-imaging data. MaxBCG primarily relies on an observational cornerstone of massive galaxy clusters: they are marked by an overdensity of bright, uniformly red galaxies. This detection scheme also exploits classical brightest cluster galaxies (BCGs), which are often found at the center of these same massive clusters. We study the algorithm herein through its performance on large, realistic, mock galaxy catalogs,
Arxiv preprint arXiv: …, 2010
We study the properties of Brightest Cluster Galaxies (BCGs) drawn from a catalogue of more than 69000 clusters in the SDSS DR6 based on the adaptive matched filter technique (AMF, Szabo et al., 2010). Our sample consists of more than 14300 galaxies in the redshift range 0.1-0.3. We test the catalog by showing that it includes well-known BCGs which lie in the SDSS footprint. We characterize the BCGs in terms of r-band luminosities and optical colours as well as their trends with redshift. In particular, we define and study the fraction of blue BCGs, namely those that are likely to be missed by either colour-based cluster surveys and catalogues, as shown by a direct comparison to maxBCG clusters that are matched in the Szabo et al. catalogue. We further compare the properties of the BCGs to those of the second and third brightest galaxies in the same cluster. Finally, we morphologically classify those galaxies hosted in the richest clusters.
Galaxy clusters in the SDSS Stripe 82 based on photometric redshifts
Astronomy & Astrophysics, 2015
Context. The discovery of new galaxy clusters is important for two reasons. First, clusters are interesting per se, since their detailed analysis allows us to understand how galaxies form and evolve in various environments and second, they play an important part in cosmology because their number as a function of redshift gives constraints on cosmological parameters. Aims. We have searched for galaxy clusters in the Stripe 82 region of the Sloan Digital Sky Survey, and analysed various properties of the cluster galaxies. Methods. Based on a recent photometric redshift (hereafter photo-z) galaxy catalogue, we built a cluster catalogue by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to fine-tune the AMACFI parameters and make the cluster detection as reliable as possible. The same method was applied to the Millennium simulation to estimate our detection efficiency and the approximate masses of the detected clusters. Considering all the cluster galaxies (i.e. within a 1 Mpc radius of the cluster to which they belong and with a photo-z differing by less than ±0.05 from that of the cluster), we stacked clusters in various redshift bins to derive colour-magnitude diagrams and galaxy luminosity functions (GLFs). For each galaxy brighter than M r < −19.0, we computed the disk and spheroid components by applying SExtractor, and by stacking clusters we determined how the disk-to-spheroid flux ratio varies with cluster redshift and mass. Results. We detected 3663 clusters in the redshift range 0.15 ≤ z ≤ 0.70, with estimated mean masses between ∼10 13 and a few 10 14 M. We cross-matched our catalogue of candidate clusters with various catalogues extracted from optical and/or X-ray data. The percentages of redetected clusters are at most 40% because in all cases we detect relatively massive clusters, while other authors detect less massive structures. By stacking the cluster galaxies in various redshift bins, we find a clear red sequence in the (g − r) versus r colour−magnitude diagrams, and the GLFs are typical of clusters, though with a possible contamination from field galaxies. The morphological analysis of the cluster galaxies shows that the fraction of late-type to early-type galaxies shows an increase with redshift (particularly in 9σ clusters) and a decrease with detection level, i.e. cluster mass. Conclusions. From the properties of the cluster galaxies, the majority of the candidate clusters detected here seem to be real clusters with typical cluster properties.
Galaxy clusters in the SDSS Stripe 82 based on galaxy photometric redshifts
2015
Context. The discovery of new galaxy clusters is important for two reasons. First, clusters are interesting per se, since their detailed analysis allows us to understand how galaxies form and evolve in various environments and second, they play an important part in cosmology because their number as a function of redshift gives constraints on cosmological parameters. Aims. We have searched for galaxy clusters in the Stripe 82 region of the Sloan Digital Sky Survey, and analysed various properties of the cluster galaxies. Methods. Based on a recent photometric redshift (hereafter photo−z) galaxy catalogue, we built a cluster catalogue by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to fine-tune the AMACFI parameters and make the cluster detection as reliable as possible. The same method was applied to the Millennium simulation to estimate our detection efficiency and the approximate masses of the detected clusters. Considering all the cluster galaxies (i.e. within a 1 Mpc radius of the cluster to which they belong and with a photo−z differing by less than ±0.05 from that of the cluster), we stacked clusters in various redshift bins to derive colour-magnitude diagrams and galaxy luminosity functions (GLFs). For each galaxy brighter than M r < −19.0, we computed the disk and spheroid components by applying SExtractor, and by stacking clusters we determined how the disk-to-spheroid flux ratio varies with cluster redshift and mass. Results. We detected 3663 clusters in the redshift range 0.15 ≤ z ≤ 0.70, with estimated mean masses between ∼ 10 13 and a few 10 14 M. We cross-matched our catalogue of candidate clusters with various catalogues extracted from optical and/or X-ray data. The percentages of redetected clusters are at most 40% because in all cases we detect relatively massive clusters, while other authors detect less massive structures. By stacking the cluster galaxies in various redshift bins, we find a clear red sequence in the (g − r) versus r colour-magnitude diagrams, and the GLFs are typical of clusters, though with a possible contamination from field galaxies. The morphological analysis of the cluster galaxies shows that the fraction of late-type to early-type galaxies shows an increase with redshift (particularly in 9σ clusters) and a decrease with detection level, i.e. cluster mass. Conclusions. From the properties of the cluster galaxies, the majority of the candidate clusters detected here seem to be real clusters with typical cluster properties.
Astronomy and Computing
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 1. As an application, we run our algorithm on a sample of X-ray cluster candidates selected from the third XMM-Newton serendipitous source catalog (3XMM-DR5) that are located in the Stripe 82 of the Sloan Digital Sky Survey (SDSS). Our method works on galaxies described in the colormagnitude feature space. We begin by examining 45 galaxy clusters with published spectroscopic redshifts in the range of 0.1 to 0.8 with a median of 0.36. As a result, we are able to identify their optical counterparts and estimate their photometric redshifts, which have a typical accuracy of 0.025 and agree with the published ones. Then, we investigate another 40 X-ray cluster candidates (from the same cluster survey) with no redshift information in the literature and found that 12 candidates are considered as galaxy clusters in the redshift range from 0.29 to 0.76 with a median of 0.57. These systems are newly discovered clusters in X-rays and optical data. Among them 7 clusters have sepectroscopic redshifts for at least one member galaxy.
A Merged Catalog of Clusters of Galaxies From Early Sloan Digital Sky Survey Data
The Astrophysical …, 2003
We present a catalog of 799 clusters of galaxies in the redshift range z est ¼ 0:05 0:3 selected from $400 deg 2 of early Sloan Digital Sky Survey (SDSS) commissioning data along the celestial equator. The catalog is based on merging two independent selection methods-a color-magnitude red-sequence maxBCG technique (B), and a hybrid matched filter method (H). The BH catalog includes clusters with richness à ! 40 (matched filter) and N gal ! 13 (maxBCG), corresponding to typical velocity dispersion of v e400 km s À1 and mass (within 0.6 h À1 Mpc radius) e5  10 13 h À1 M . This threshold is below Abell richness class 0 clusters. The average space density of these clusters is 2  10 À5 h 3 Mpc À3 . All NORAS X-ray clusters and 53 of the 58 Abell clusters in the survey region are detected in the catalog; the five additional Abell clusters are detected below the BH catalog cuts. The cluster richness function is determined and found to exhibit a steeply decreasing cluster abundance with increasing richness. We derive observational scaling relations between cluster richness and observed cluster luminosity and cluster velocity dispersion; these scaling relations provide important physical calibrations for the clusters. The catalog can be used for studies of individual clusters, for comparisons with other sources such as X-ray clusters and active galactic nuclei, and, with proper correction for the relevant selection functions, also for statistical analyses of clusters.
20-10-2004 RCS043938-2904.9: A New Rich Cluster of Galaxies at z = 0.951 1
2004
We present deep I, Js, Ks imaging and optical spectroscopy of the newly discovered Red-Sequence Cluster Survey cluster RCS043938-2904.9. This cluster, drawn from an extensive preliminary list, was selected for detailed study on the basis of its apparent optical richness. Spectroscopy of 11 members places the cluster at z = 0.951±0.006, and confirms the photometric redshift estimate from the (R-z) color-magnitude diagram. Analysis of the infrared imaging data demonstrates that the cluster is extremely rich, with excess counts in the Ks-band exceeding the expected background counts by 9σ. The properties of the galaxies in RCS043938-2904.9 are consistent with those seen in other clusters at similar redshifts. Specifically, the red-sequence color, slope and scatter, and the sizemagnitude relation of these galaxies are all consistent with that seen in the few other high redshift clusters known, and indeed are consistent with appropriately evolved properties of local cluster galaxies. The...
A Merged Catalog of Clusters of Galaxies from Early SDSS Data
2003
We present a catalog of 799 clusters of galaxies in the redshift range z_est = 0.05 - 0.3 selected from ~400 deg^2 of early SDSS commissioning data along the celestial equator. The catalog is based on merging two independent selection methods -- a color-magnitude red-sequence maxBCG technique (B), and a Hybrid Matched-Filter method (H). The BH catalog includes clusters with richness \Lambda >= 40 (Matched-Filter) and N_gal >= 13 (maxBCG), corresponding to typical velocity dispersion of \sigma_v >~ 400 km s^{-1} and mass (within 0.6 h^{-1) Mpc radius) >~ 5*10^{13} h^{-1} M_sun. This threshold is below Abell richness class 0 clusters. The average space density of these clusters is 2*10^{-5} h^3 Mpc^{-3}. All NORAS X-ray clusters and 53 of the 58 Abell clusters in the survey region are detected in the catalog; the 5 additional Abell clusters are detected below the BH catalog cuts. The cluster richness function is determined and found to exhibit a steeply decreasing cluster abundance with increasing richness. We derive observational scaling relations between cluster richness and observed cluster luminosity and cluster velocity dispersion; these scaling relations provide important physical calibrations for the clusters. The catalog can be used for studies of individual clusters, for comparisons with other sources such as X-ray clusters and AGNs, and, with proper correction for the relevant selection functions, also for statistical analyses of clusters.
Precision Measurements of the Cluster Red Sequence Using An Error Corrected Gaussian Mixture Model
2011
The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increase mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using -2similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment. These precise measurements serve as an important observational check on simulations and mock galaxy catalogs. The observed trends in the slope and scatter of the red sequence ridgeline with redshift are clues to possible intrinsic evolution of the cluster red-sequence itself. Most importantly, the methods presented in this work lay the groundwork for further improvements in optically-based cluster cosmology.