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Register a new userA GMBCG Galaxy Cluster Catalog of 55,424 Rich Clusters from SDSS DR7
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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.
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We present a new catalog of spectroscopically-confirmed white dwarf stars from the Sloan Digital Sky Survey Data Release 7 spectroscopic catalog. We find 20,407 white dwarf spectra, representing 19,712 stars, and provide atmospheric model fits to 14,120 DA and 1011 DB white dwarf spectra from 12,843 and 923 stars, respectively. These numbers represent a more than factor of two increase in the total number of white dwarf stars from the previous SDSS white dwarf catalog based on DR4 data. Our distribution of subtypes varies from previous catalogs due to our more conservative, manual classifications of each star in our catalog, supplementing our automatic fits. In particular, we find a large number of magnetic white dwarf stars whose small Zeeman splittings mimic increased Stark broadening that would otherwise result in an overestimated log(g) if fit as a non-magnetic white dwarf. We calculate mean DA and DB masses for our clean, non-magnetic sample and find the DB mean mass is statistically larger than that for the DAs.
Recent studies have shown that the cross-correlation coefficient between galaxies and dark matter is very close to unity on scales outside a few virial radii of galaxy halos, independent of the details of how galaxies populate dark matter halos. This finding makes it possible to determine the dark matter clustering from measurements of galaxy-galaxy weak lensing and galaxy clustering. We present new cosmological parameter constraints based on large-scale measurements of spectroscopic galaxy samples from the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7). We generalise the approach of Baldauf et al. (2010) to remove small scale information (below 2 and 4 Mpc/h for lensing and clustering measurements, respectively), where the cross-correlation coefficient differs from unity. We derive constraints for three galaxy samples covering 7131 sq. deg., containing 69150, 62150, and 35088 galaxies with mean redshifts of 0.11, 0.28, and 0.40. We clearly detect scale-dependent galaxy bias for the more luminous galaxy samples, at a level consistent with theoretical expectations. When we vary both sigma_8 and Omega_m (and marginalise over non-linear galaxy bias) in a flat LCDM model, the best-constrained quantity is sigma_8 (Omega_m/0.25)^{0.57}=0.80 +/- 0.05 (1-sigma, stat. + sys.), where statistical and systematic errors have comparable contributions, and we fixed n_s=0.96 and h=0.7. These strong constraints on the matter clustering suggest that this method is competitive with cosmic shear in current data, while having very complementary and in some ways less serious systematics. We therefore expect that this method will play a prominent role in future weak lensing surveys. When we combine these data with WMAP7 CMB data, constraints on sigma_8, Omega_m, H_0, w_{de} and sum m_{ u} become 30--80 per cent tighter than with CMB data alone, since our data break several parameter degeneracies.
Based on galaxies from the Sloan Digital Sky Survey (SDSS) and subhalos in the corresponding reconstructed region from the constrained simulation of ELUCID, we study the alignment of central galaxies relative to their host groups in the group catalog, as well as the alignment relative to the corresponding subhalos in the ELUCID simulation. Galaxies in observation are matched to dark matter subhalos in the ELUCID simulation using a novel neighborhood abundance matching method. In observation, the major axes of galaxies are found to be preferentially aligned to the major axes of their host groups. There is a color dependence of galaxy-group alignment that red centrals have a stronger alignment along the major axes of their host groups than blue centrals. Combining galaxies in observation and subhalos in the ELUCID simulation, we also find that central galaxies have their major axes to be aligned to the major axes of their corresponding subhalos in the ELUCID simulation. We find that the galaxy-group and galaxy-subhalo alignment signals are stronger for galaxies in more massive halos. We find that the alignments between main subhalos and the SDSS matched subhalo systems in simulation are slightly stronger than the galaxy-group alignments in observation.
Using the k-means cluster analysis algorithm, we carry out an unsupervised classification of all galaxy spectra in the seventh and final Sloan Digital Sky Survey data release (SDSS/DR7). Except for the shift to restframe wavelengths, and the normalization to the g-band flux, no manipulation is applied to the original spectra. The algorithm guarantees that galaxies with similar spectra belong to the same class. We find that 99 % of the galaxies can be assigned to only 17 major classes, with 11 additional minor classes including the remaining 1%. The classification is not unique since many galaxies appear in between classes, however, our rendering of the algorithm overcomes this weakness with a tool to identify borderline galaxies. Each class is characterized by a template spectrum, which is the average of all the spectra of the galaxies in the class. These low noise template spectra vary smoothly and continuously along a sequence labeled from 0 to 27, from the reddest class to the bluest class. Our Automatic Spectroscopic K-means-based (ASK) classification separates galaxies in colors, with classes characteristic of the red sequence, the blue cloud, as well as the green valley. When red sequence galaxies and green valley galaxies present emission lines, they are characteristic of AGN activity. Blue galaxy classes have emission lines corresponding to star formation regions. We find the expected correlation between spectroscopic class and Hubble type, but this relationship exhibits a high intrinsic scatter. Several potential uses of the ASK classification are identified and sketched, including fast determination of physical properties by interpolation, classes as templates in redshift determinations, and target selection in follow-up works (we find classes of Seyfert galaxies, green valley galaxies, as well as a significant number of outliers). The ASK classification is publicly accessible through various websites.
Utilizing the SDSS-DR13 spectroscopic dataset, we create a new publicly-available catalog of 1,800 galaxy clusters (GalWeight cluster catalog, $mathtt{GalWCat19}$) and a corresponding catalog of 34,471 identified member galaxies. The clusters are identified from overdensities in redshift-phase space. The GalWeight technique introduced in Abdullah, Wilson and Klypin (AWK18) is then applied to identify cluster members. The completeness of the cluster catalog ($mathtt{GalWCat19}$) and the procedure followed to determine cluster mass are tested on the Bolshoi N-body simulations. The 1,800 $mathtt{GalWCat19}$ clusters range in redshift between $0.01 - 0.2$ and in mass between $(0.4 - 14) times 10^{14}h^{-1}M_{odot}$. The cluster catalog provides a large number of cluster parameters including sky position, redshift, membership, velocity dispersion, and mass at overdensities $Delta = 500, 200, 100, 5.5$. The 34,471 member galaxies are identified within the radius at which the density is 200 times the critical density of the Universe. The galaxy catalog provides the coordinates of each galaxy and the ID of the cluster that the galaxy belongs to. The cluster velocity dispersion scales with mass as $log(sigma_{200})=log(946pm52~ mbox{km} ~ mbox{s}^{-1}) +(0.349pm0.142)logleft[h(z) ~ M_{200}/10^{15}M_odotright]$ with scatter of $delta_{logsigma} = 0.06$. The catalogs are publicly available at the following websitefootnote{url{https://mohamed-elhashash-94.webself.net/galwcat/}}.
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