The Cut & Enhance method : selecting clusters of galaxies from the SDSS commissioning data

We describe an automated method, the Cut & Enhance method (CE) for detecting clusters of galaxies in multi-color optical imaging surveys. This method uses simple color cuts, combined with a density enhancement algorithm, to up-weight pairs of galaxies that are close in both angular separation and color. The method is semi-parametric since it uses minimal assumptions about cluster properties in order to minimize possible biases. No assumptions are made about the shape of clusters, their radial profile or their luminosity function. The method is successful in finding systems ranging from poor to rich clusters of galaxies, of both regular and irregular shape. We determine the selection function of the CE method via extensive Monte Carlo simulations which use both the real, observed background of galaxies and a randomized background of galaxies. We use position shuffled and color shuffled data to perform the false positive test. We have also visually checked all the clusters detected by the CE method. We apply the CE method to the 350 deg^2 of the SDSS (Sloan Digital Sky Survey) commissioning data and construct a SDSS CE galaxy cluster catalog with an estimated redshift and richness for each cluster. The CE method is compared with other cluster selection methods used on SDSS data such as the Matched Filter (Postman et al. 1996, Kim et al. 2001), maxBCG technique (Annis et al. 2001) and Voronoi Tessellation (Kim et al. 2001). The CE method can be adopted for cluster selection in any multi-color imaging surveys.Comment: 62 pages, 32 figures, Accepted for publication in the Astronomical Journal, "the CE galaxy cluster catalog can be downloaded from, http://astrophysics.phys.cmu.edu/~tomo/ce/

SDSS-RASS: Next Generation of Cluster-Finding Algorithms

We outline here the next generation of cluster-finding algorithms. We show how advances in Computer Science and Statistics have helped develop robust, fast algorithms for finding clusters of galaxies in large multi-dimensional astronomical databases like the Sloan Digital Sky Survey (SDSS). Specifically, this paper presents four new advances: (1) A new semi-parametric algorithm - nicknamed ``C4'' - for jointly finding clusters of galaxies in the SDSS and ROSAT All-Sky Survey databases; (2) The introduction of the False Discovery Rate into Astronomy; (3) The role of kernel shape in optimizing cluster detection; (4) A new determination of the X-ray Cluster Luminosity Function which has bearing on the existence of a ``deficit'' of high redshift, high luminosity clusters. This research is part of our ``Computational AstroStatistics'' collaboration (see Nichol et al. 2000) and the algorithms and techniques discussed herein will form part of the ``Virtual Observatory'' analysis toolkit.Comment: To appear in Proceedings of MPA/MPE/ESO Conference "Mining the Sky", July 31 - August 4, 2000, Garching, German

An Optical Catalog of Galaxy Clusters Obtained from an Adaptive Matched Filter Finder Applied to SDSS DR6

We present a new cluster catalog extracted from the Sloan Digital Sky Survey Data Release 6 (SDSS DR6) using an adaptive matched filter (AMF) cluster finder. We identify 69,173 galaxy clusters in the redshift range 0.045 $\le z <$ 0.78 in 8420 sq. deg. of the sky. We provide angular position, redshift, richness, core and virial radii estimates for these clusters, as well as an error analysis for each of these quantities. We also provide a catalog of more than 205,000 galaxies representing the three brightest galaxies in the $r$ band which are possible BCG candidates. We show basic properties of the BCG candidates and study how their luminosity scales in redshift and cluster richness. We compare our catalog with the maxBCG and GMBCG catalogs, as well as with that of Wen, Han, and Liu. We match between 30% and 50% of clusters between catalogs over all overlapping redshift ranges. We find that the percentage of matches increases with the richness for all catalogs. We cross match the AMF catalog with available X-ray data in the same area of the sky and find 539 matches, 119 of which with temperature measurements. We present scaling relations between optical and X-ray properties and cluster center comparison. We find that both $\Lambda_{200}$ and $R_{200}$ correlate well with both $L_X$ and $T_X$, with no significant difference in trend if we restrict the matches to flux-limited X-ray samples.Comment: 59 pages, 28 figures; accepted for publication in The Astrophysical Journa

Tracking Performance of the Scintillating Fiber Detector in the K2K Experiment

The K2K long-baseline neutrino oscillation experiment uses a Scintillating Fiber Detector (SciFi) to reconstruct charged particles produced in neutrino interactions in the near detector. We describe the track reconstruction algorithm and the performance of the SciFi after three years of operation.Comment: 24pages,18 figures, and 1 table. Preprint submitted to NI

A GMBCG Galaxy Cluster Catalog of 55,424 Rich Clusters from SDSS DR7

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.Comment: Updated to match the published version. The catalog can be accessed from: http://home.fnal.gov/~jghao/gmbcg_sdss_catalog.htm

Grizzly Bear Abundance and Density in The Cabinet-Yaak Ecosystem

We use genetic detection data from concurrent hair corral and bear rub sampling to provide abundance and density estimates for the threatened grizzly bear (Ursus arctos) populations in the Cabinet Mountain and Yaak regions in northwestern Montana and northern Idaho collectively known as the Cabinet-Yaak Ecosystem (CYE). We used Huggins models in Program MARK and model averaging to generate region- and sex-specific abundance estimates. To estimate the average number of bears present, we estimated mean bear residency on our sampling grid from telemetry data and used it to correct our super population estimates for lack of geographic closure. Total grizzly bear abundance in the CYE in 2012 was 49 (95% CI: 44-62) with an average of 45 (95% CI: 42-65) present at any one time. Population size in the Cabinet and Yaak regions was equal: Cabinet: 22 (95% CI: 20-36); Yaak: 22 (95% CI: 22-39). Grizzly bear density in the CYE was 4.5 (95% CI: 3.7-5.3) grizzly bears/1000 km2. With parentage analysis, we document the first natural migrants to the critically low and interbred Cabinet population and the Yaak population by bears born to parents in neighboring populations. These events support data from other sources suggesting that the expansion of neighboring populations may eventually help sustain the CYE populations

Composite Luminosity Functions Based on the Sloan Digital Sky Survey "Cut & Enhance" Galaxy Cluster Catalog

We present here results on the composite luminosity functions of galaxies in the clusters of galaxies selected from the SDSS Cut and Enhance cluster catalog (CE; Goto et al. 2001). We construct the composite luminosity function in the five SDSS bands, u,g,r,i and z, using 204 CE clusters ranging from z=0.02 to z=0.25. We use photometric redshifts to construct composite luminosity functions. The robustness of the weighting scheme was tested using Monte Carlo simulation. We find the slope of composite LFs become flatter toward redder color band. Comparing with field LFs of SDSS (Blanton et al. 2001), cluster LFs have brighter characteristic magnitude and flatter slopes in g, r, i and z bands. These results are consistent with the hypothesis that the cluster LF has two distinct underlying populations i.e. the bright end of the LF is dominated by bright early types that follow a gaussian--like luminosity distribution, while the faint--end of the cluster LF is a steep power--law like function dominated by star--forming (bluer) galaxies. We also study the composite luminosity functions for early--type and late--type galaxies using profile fits, a concentration parameter and u-r color to classify galaxy morphology. The strong dependence of LF on galaxy morphology is found.The faint end slope of the LF is always flatter for early--type galaxies than late--type regardless of passband and methodology. These results are consistent with the hypothesis that the cluster region are dominated by bright elliptical galaxies.Comment: 21 pages, 5 figures, PASJ, 54, 515, miner typos fixe