The Cut-and-Enhance Method: Selecting Clusters of Galaxies from the Sloan Digital Sky Survey Commissioning Data

By Tomotsugu Goto, M. Sekiguchi, Robert Nichol, N. Bahcall, R. Kim, James Annis, Željko Ivezic´, J. Brinkmann, G. Hennessy, G. Szokoly and 1 more. 2001

159 citations recorded by the source corpus.

We describe an automated method, the cut-and-enhance (CE) method, for detecting clusters of galaxies in multicolor 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 semiparametric, 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 that use both the real, observed background of galaxies and a randomized background of galaxies. We use position-shuffled and color-shuffled data to perform false-positive tests. We have also visually checked all the clusters detected by the CE method. We apply the CE method to the 350 deg2 of the Sloan Digital Sky Survey (SDSS) commissioning data and construct an 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, "maxBCG," and Voronoi tessellation techniques. The CE method can be adopted for cluster selection in any multicolor imaging survey.

Subfields: Astronomy and Astrophysics, Computer Vision and Pattern Recognition, Ecology

View Paper: https://www.semanticscholar.org/paper/9c9fd53644411813157e56e8c81337bba4fb1a0a

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Citations in the corpus

GALAXY CLUSTERS IDENTIFIED FROM THE SDSS DR6 AND THEIR PROPERTIES (2009, methodology): “The luminosity function of galaxies in a cluster is taken to follow the Schechter function (Schechter 1976) φ(M)dM ∝ 10−0.4(M−M ∗)(α+1) exp[−10−0.4(M−M ∗)]dM. (4) We adopt the parameters as,α = −0.85 ± 0.03, M∗ = −22.21 ± 0.05, derived by Goto et al. (2002b) based on the SDSS CE clusters.”
Measurement of Galaxy Cluster Sizes, Radial Profiles, and Luminosity Functions from SDSS Photometric Data (2004, background): “We recover a luminosity function that is comparable to that of rich clusters found by Goto et al. (2002), who used different cluster-finding and background subtraction algorithms with the same sample of SDSS data used in this paper.”
CARS: the CFHTLS-Archive-Research Survey. I. Five-band multi-colour data from 37 sq. deg. CFHTLS-wid (2008, background): “…& Böhringer 2002; Böhringer et al. 2004; Mantz et al. 2007) and in the optical (see e.g. Postman et al. 1996; Olsen et al. 1999; Gladders & Yee 2000; Goto et al. 2002; Bahcall et al. 2003; Gladders et al. 2007; Koester et al. 2007); see also Gal (2008) for a concise review of various cluster…”
A GMBCG GALAXY CLUSTER CATALOG OF 55,424 RICH CLUSTERS FROM SDSS DR7 (2010, methodology): “Inserting model clusters into a realistic background is a widely used method to create mock cat- alogs for evaluating cluster finding algorithms (Diaferio et al. 1999; Adami et al. 2000; Postman et al. 2002; Kim et al. 2002; Goto et al. 2002; Koester et al. 2007a).”
Detection of large-scale intrinsic ellipticity—density correlation from the Sloan Digital Sky Survey and implications for weak lensing surveys (2005, background): “A variety of algorithms exist to identify clusters and their BCGs (e.g. Gladders & Yee 2000; Goto et al. 2002; Bahcall et al. 2003), and it is beyond the scope of this paper to examine how much the density-shape correlation can be suppressed by rejecting BCGs selected by each of these methods.”
The XMM Cluster Survey:Optical analysis methodology and the first data release (2011, background): “This large fraction is a reflection of the fact that much of our redshift follow-up to date (June 2011) has come from the SDSS, and there are by now several optically selected cluster catalogues covering the SDSS footprint, e.g. MaxBCG, Koester et al. (2007a) and Cut-and-Enhance, Goto et al. (2002).”
A MaxBCG Catalog of 13,823 Galaxy Clusters from the Sloan Digital Sky Survey (2007, background): “Initial efforts at photometric selection of clusters were presented in Goto et al. (2002) and Bahcall et al. (2003).”
266 E+A galaxies selected from the Sloan Digital Sky Survey Data Release 2: the origin of E+A galaxies (2005, methodology): “As a reference, we plot the density distributions of cluster galaxies found in Goto et al. (2004c; see also Goto et al. 2002a,b for a cluster catalog) in the dotted line.”
The Red-Sequence Cluster Survey. I. The Survey and Cluster Catalogs for Patches RCS 0926+37 and RCS 1327+29 (2004, methodology): “…(Postman et al. 1996) and its variants (Kepner et al. 1999; Lobo et al. 2000; Kim et al. 2002), methods relying primarily on searches for the early-type galaxy population (Ostrander et al. 1998; Goto et al. 2002), and the search for the unresolved background light of the cluster (Dalcanton 1996).”
THE REDMAPPER GALAXY CLUSTER CATALOG FROM DES SCIENCE VERIFICATION DATA (2016, background): “There are already a wide range of photometric cluster finders (e.g. Goto et al. 2002; Gladders et al. 2007; Koester et al. 2007a; Hao et al. 2010; Soares-Santos et al. 2011; Szabo et al. 2011; Wen et al. 2012; Murphy et al. 2012; Ascaso et al. 2012, 2014; Oguri 2014), each with various strengths…”
redMaPPer. I. ALGORITHM AND SDSS DR8 CATALOG (2013, background): “The cluster finding algorithm can then be rerun, and one can determine which clusters are detected, and how many “false” clusters are detected (e.g., Goto et al. 2002; Koester et al. 2007b; Hao et al. 2010a).”
The C4 Clustering Algorithm: Clusters of Galaxies in the Sloan Digital Sky Survey (2005, methodology): “Previous authors have realized the necessity of such a detailed understanding of their clustering algorithms (e.g., Diaferio et al. 1999, Adami et al. 2000, Postman et al. 2002, Kim et al. 2002, Goto et al. 2002, and Eke et al. 2004).”
The Atacama Cosmology Telescope: A Catalog of >4000 Sunyaev–Zel’dovich Galaxy Clusters (2020, background): “Half of the missing 21 clusters were previously reported in other catalogs (Goto et al. 2002; Lopes et al. 2004; Durret et al. 2011; Menanteau et al. 2013; Rykoff et al. 2014; Wen & Han 2015).”
The Atacama Cosmology Telescope: Sunyaev-Zel'dovich selected galaxy clusters at 148 GHz from three seasons of data (2013, methodology): “There is a long history of using optical (e.g., Abell 1958; Lumsden et al. 1992; Goto et al. 2002; Lopes et al. 2004; Miller et al. 2005; Koester et al. 2007; Hao et al. 2010; Szabo et al. 2011; Wen et al. 2009, 2012) and X-ray (e.g., Henry et al. 1992; Böhringer et al. 2004; Burenin et al. 2007;…”
Galaxy Star Formation as a Function of Environment in the Early Data Release of the Sloan Digital Sky Survey (2002, unknown): “This non-parametric approach significantly reduces the risk of biasing our cluster sample because we are not modeling the expected colors of the cluster galaxy population (Gladders & Yee 2000; Goto et al. 2002).”
Galaxy Groups in the SDSS DR4. I. The Catalog and Basic Properties (2007, methodology): “Goto et al. (2002) developed a cut-and-enhance method and applied it to the early SDSS commissioning data.”
A CATALOG OF 132,684 CLUSTERS OF GALAXIES IDENTIFIED FROM SLOAN DIGITAL SKY SURVEY III (2012, methodology): “Galaxy clusters or groups have been found by using the SDSS spectroscopic data (e.g., Merchán & Zandivarez 2005; Berlind et al. 2006) and the photometric data (e.g., Goto et al. 2002; Koester et al. 2007a; Wen et al. 2009; Hao et al. 2010; Szabo et al. 2011).”
Percolation Galaxy Groups and Clusters in the SDSS Redshift Survey: Identification, Catalogs, and the Multiplicity Function (2006, methodology): “All these techniques were applied to the early SDSS commissioning data (Bahcall et al. 2003; Goto et al. 2002).”