SDSS DR7 Superclusters Morphology

A&A 532, A5 (2011) Astronomy DOI: 10.1051/0004-6361/201116564 & c ESO 2011 Astrophysics SDSS DR7 superclusters Morphology M. Einasto1,L.J.Liivamägi1,2,E.Tago1,E.Saar1,E.Tempel1,2,J.Einasto1, V. J. Martínez3, and P. Heinämäki4 1 Tartu Observatory, 61602 Tõravere, Estonia e-mail: [email protected] 2 Institute of Physics, Tartu University, Tähe 4, 51010 Tartu, Estonia 3 Observatori Astronòmic, Universitat de València, Apartat de Correus 22085, 46071 València, Spain 4 Tuorla Observatory, University of Turku, Väisäläntie 20, Piikkiö, Finland Received 24 January 2011 / Accepted 2 May 2011 ABSTRACT Aims. We study the morphology of a set of superclusters drawn from the SDSS DR7. Methods. We calculate the luminosity density field to determine superclusters from a flux-limited sample of galaxies from SDSS DR7 and select superclusters with 300 and more galaxies for our study. We characterise the morphology of superclusters using the fourth Minkowski functional V3, the morphological signature (the curve in the shapefinder’s K1-K2 plane) and the shape parameter (the ratio of the shapefinders K1/K2). We investigate the supercluster sample using multidimensional normal mixture modelling. We use Abell clusters to identify our superclusters with known superclusters and to study the large-scale distribution of superclusters. Results. The superclusters in our sample form three chains of superclusters; one of them is the Sloan Great Wall. Most superclusters have filament-like overall shapes. Superclusters can be divided into two sets; more elongated superclusters are more luminous, richer, have larger diameters and a more complex fine structure than less elongated superclusters. The fine structure of superclusters can be divided into four main morphological types: spiders, multispiders, filaments, and multibranching filaments. We present the 2D and 3D distribution of galaxies and rich groups, the fourth Minkowski functional, and the morphological signature for all superclusters. Conclusions. Widely different morphologies of superclusters show that their evolution has been dissimilar. A study of a larger sample of superclusters from observations and simulations is needed to understand the morphological variety of superclusters and the possible connection between the morphology of superclusters and their large-scale environment. Key words. cosmology: observations – large-scale structure of Universe – galaxies: clusters: general 1. Introduction Recently, the XMM-Newton satellite follow-up for the valida- tion of Planck cluster candidates led to the discovery of two The most remarkable feature of the megaparsec-scale matter dis- massive, previously unknown superclusters of galaxies (Planck tribution in the Universe is the presence of the cosmic web – the Collaboration et al. 2011). These are likely the first superclusters network of galaxies, groups, and clusters connected by filaments discovered through the Sunyaev-Zeldovich effect. (Joeveer et al. 1978; Gregory & Thompson 1978; Zeldovich Superclusters are important tracers of dark and baryonic mat- et al. 1982; de Lapparent et al. 1986). The formation of a web of ter in the Universe (Zappacosta et al. 2005; Génova-Santos et al. galaxies and systems of galaxies is predicted in any physically 2005; Heymans et al. 2008; Buote et al. 2009; Padilla-Torres motivated theory of the formation of structure in the Universe et al. 2009; Schirmer et al. 2011). Studies of superclusters and (see, e.g., Bond et al. 1996). In this scenario galaxies and galaxy of the supercluster-void network have demonstrated the presence systems form because of initial density perturbations on dif- of a characteristic scale in the distribution of rich superclusters −1 ferent scales. Perturbations on a scale of about 100 h Mpc (Einasto et al. 1994, 1997a). This was probably an early hint of = −1 −1 (H0 100 h km s Mpc ) give rise to the largest systems of baryon acoustic oscillations (Hütsi 2010). galaxies – rich superclusters. At larger scales dynamical evolu- To search for superclusters and to understand their proper- tion proceeds at a slower rate and superclusters have retained the ties, we need to know how to identify them and how to quantify memory of the initial conditions of their formation and of the their properties (Bond et al. 2010). Several methods have been early evolution of structure (Einasto et al. 1980; Zeldovich et al. proposed to study the cosmic web (Bharadwaj et al. 2004; Stoica 1982; Kofman et al. 1987). et al. 2010; Aragón-Calvo et al. 2010; Sousbie 2011; Sousbie Numerical simulations show that high-density peaks in the et al. 2011, and references therein). One approach is to deter- density distribution (the seeds of supercluster cores) are seen mine cosmic structures (in our study – superclusters of galax- already at very early stages of the formation and evolution of ies) using the density field and to study their morphology with structure (Einasto 2010). These are the locations of the forma- Minkowski functionals and shapefinders (Schmalzing & Buchert tion of the first objects in the Universe (e.g. Venemans et al. 1997; Sathyaprakash et al. 1998; Basilakos 2003; Sheth et al. 2004; Mobasher et al. 2005; Ouchi et al. 2005). Observations 2003; Shandarin et al. 2004; Einasto et al. 2007d, and refer- have already found superclusters at high redshifts (Nakata et al. ences therein). Oort (1983) gave a review of the early studies of 2005; Swinbank et al. 2007; Gal et al. 2008; Tanaka et al. 2009). superclusters. Supercluster catalogues compiled based on data Article published by EDP Sciences A5, page 1 of 20 A&A 532, A5 (2011) about clusters of galaxies were published by Zucca et al. (1993); sets using multidimensional normal mixture modelling, apply- Einasto et al. (1994); Kalinkov & Kuneva (1995); Einasto et al. ing the Mclust package for clustering and classification (Fraley (2001). Recent deep surveys of galaxies (as 2dFGRS and SDSS, & Raftery 2006) from R, an open-source free statistical envi- see Colless et al. 2003; Abazajian et al. 2009) introduced a new ronment developed under the GNU GPL (Ihaka & Gentleman era in the studies of the large-scale structure of the Universe, 1996, http://www.r- project.org). The cluster member- where systems of galaxies can be studied in unprecedended de- ship of superclusters and their large-scale distribution is anal- tail. A number of supercluster catalogues have been compiled ysed, and a short description of individual superclusters is given. with these data (Basilakos 2003; Einasto et al. 2003a; Erdogdu˘ The data are described in Sect. 2, the methods in Sect. 3,andthe et al. 2004; Einasto et al. 2006, 2007b; Liivamägi et al. 2010; results in Sect. 4. In Sect. 5 the selection effects in our sample Luparello et al. 2011, and references therein). are discussed, and a comparison with other studies is given. The The overall morphology of superclusters has been studied study is summarised in Sect. 6. Interactive 3D models of the rich- by several authors (Kolokotronis et al. 2002; Basilakos 2003; est superclusters in our sample can be found on our web page: Costa-Duarte et al. 2011), we refer to Einasto et al. (2007a) http://www.aai.ee/∼maret/SDSSsclmorph.html. for a review of the properties of superclusters. The shapes and We assume the standard cosmological parameters: the −1 −1 sizes of superclusters can be used to compare the observed su- Hubble parameter H0 = 100 h km s Mpc , the matter den- perclusters with those obtained from cosmological simulations sity Ωm = 0.27, and the dark energy density ΩΛ = 0.73. (Kolokotronis et al. 2002; Einasto et al. 2007a). Nichol et al. (2006) showed that the higher order correlation functions of the 2dFGRS do not agree with those found in numerical simulations 2. Data (but this fact can be explained by non-Gaussian initial density We selected the MAIN galaxy sample of the 7th data release of fields, Gaztanaga & Maehoenen 1996). This discrepancy may be the Sloan Digital Sky Survey (Adelman-McCarthy et al. 2008; caused by the unusual morphology of one of the richest super- Abazajian et al. 2009) with the apparent r magnitudes 12.5 ≤ clusters in the 2dFGRS, the supercluster SCl 126 (Einasto et al. r ≤ 17.77, excluding duplicate entries. The sample is described 2007d, 2008) from the catalogue of superclusters by Einasto in detail in Tago et al. (2010, hereafter T10). We corrected the et al. (2001, hereafter E01). The morphology of superclus- ff redshifts of galaxies for the motion relative to the CMB and com- ters may be used to distinguish between di erent cosmological puted the co-moving distances (Martínez & Saar 2002) of galax- models (Kolokotronis et al. 2002). ies. Superclusters contain structures with a wide range of densi- The absolute magnitudes of galaxies are determined in the ties, from high-density cores of rich clusters to low-density fila- r-band M with k-correction for the SDSS galaxies calculated ments between clusters and groups. This makes them ideal lab- r ff with the KCORRECT algorithm (Blanton et al. 2003a; Blanton oratories to study processes that a ect the evolution of galaxies, & Roweis 2007). In addition, we applied the evolution correc- groups, and clusters of galaxies. A number of studies have al- ff tions, using the luminosity evolution model of Blanton et al. ready shown that the supercluster environment a ects the prop- (2003b). The magnitudes correspond to the rest-frame at the red- erties of galaxies, groups, and clusters located there (Einasto shift z = 0. et al. 2003b; Plionis 2004; Wolf et al. 2005; Haines et al. 2006; The first step is to determine groups and clusters of galaxies Einasto et al. 2007c; Porter et al. 2008; Tempel et al. 2009; with the friends-of-friends algorithm, where a galaxy belongs to Fleenor & Johnston-Hollitt 2010; Tempel et al. 2011; Einasto a group of galaxies if this galaxy has at least one group member et al.

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