A Catalogue of Galaxy Clusters and Groups as the Basis for a New Galaxy Supercluster Catalogue

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1 A Catalogue of Galaxy Clusters and Groups as the Basis for a New Galaxy Supercluster Catalogue Elena Panko Department of Astronomy, Odessa National University T. G. Shevchenko Park, Odessa 65014, Ukraine Abstract. A sample of 6188 nearby galaxy structures in the southern sky, complete to r F = 18 m.3 and each containing at least 10 members, was tested for its usefulness in detecting galaxy superclusters. It is shown that the richest galaxy clusters, those containing at least 50 members, match the large-scale distribution of galaxies, while a subsample of 1746 galaxy clusters with estimated redshifts up to 0.12 can be used to create a catalogue of galaxy superclusters as well as a list of separated galaxy clusters for future statistical analysis. Keywords: large-scale structure galaxy superclusters galaxy clusters PACS: , r, Dx INTRODUCTION The distribution of galaxy superclusters, the largest structures in the Universe, reflects the largest initial density perturbations on a characteristic scale of 100 h 1 Mpc. Galaxy supercluster catalogues based upon the ACO galaxy clusters catalogue [1] were created by Zucca et al. [2] and Einasto at al. [3]. Later Einasto et al. [4] described superclusters of galaxies using the 2dF redshift survey as input. Einasto et al. [5] also used the APM galaxy clusters catalogue [6] for supercluster searches. We discuss the possibility of creating a catalogue of galaxy superclusters using another source: the Catalogue of Galaxy Clusters and Groups [7] (hereafter PF), which is based upon the galaxy catalogue of the Muenster Red Sky Survey [8]. The paper is organized in the standard fashion. Section 2 presents the observational data, Section 3 describes the distance calibration and the selection of a richness limit, Section 4 describes the method of searching for superclusters, and conclusions are given at the end. OBSERVATIONAL DATA The PF Catalogue of galaxy structures [7] is the observational basis for the present study. The catalogue was created using data from the Muenster Red Sky Survey [8], which is a homogeneous large-scale galaxy catalogue covering an area of about 5000 square degrees in the southern hemisphere, complete to a magnitude limit of r F = 18 m.3. The same r F magnitude limit defines the completeness limit for galaxies in the PF structures. The Muenster Red Sky Survey galaxy catalogue is the result of scanning 217 ESO plates 417

2 with galactic latitudes of b < 45. All non-galaxy objects were convincingly removed in our subsequent analysis. The 2D Voronoi tessellation technique ([9],[10],[11]) was applied to the galaxy catalogue to search for overdense regions. That methodology makes it possible to extract structures containing different numbers of galaxies and with various shapes within the same statistical approach. The resulting PF catalogue includes 6188 such structures, with at least 10 galaxies in each structure field. The richness, area, major and minor semiaxes, and ellipticity parameter of the best ellipse are given in the PF catalogue for each structure. Unfortunately, the resulting catalogue does not contain redshifts for galaxies, so the PF structures require a distance calibration. DISTANCE CALIBRATION In order to estimate distances for the PF structures, we calibrated the logz m relation following Dalton et al. [6], using the magnitude of the tenth brightness galaxy m 10 as m in the calibration. The first step of the procedure was to compare the positions of the structure centers, as given in the PF, with those in the ACO and APM cluster catalogues. If the distance between the centers of the PF and ACO clusters was less than 0.5 of the PF equivalent cluster radius, the two objects were regarded as identical. More than 1000 and 600 such matches were found, respectively. The resulting calibration from the analysis was found to be: logz est = m 10, based upon 455 data points from the ACO comparison and 374 from the APM comparison, since only those clusters have measured redshifts z. A Kolmogorov-Smirnov test indicates that structures containing more than 50 members in the structure field (N g ) are taken from the some population, in other words the structure ellipticity distributions are identical [12]. We selected those 1746 clusters with redshift distance estimates for a superclusters search; however. The resulting large-scale structure is described in detail on the basis of both rich and poor clusters. The positions of the clusters are shown in Fig. 1, while the distribution of their z est is shown in Fig. 2. For subsequent analysis we have 1746 PF structures with N g 50, including 1254 with 50 N g 100, 377 with N g in the limits , 76 with N g in the limits , 27 with , and 12 containing more than 400 galaxies in the cluster field. THE METHOD OF SUPERCLUSTER SEARCHING We selected a method of analysis that combined results obtained by the 3D Voronoi Tessellation Technique (VTT) with those using the Friend-of-Friend method (FoF). Melnyk, Elyiv and Vavilova successfully applied the 3D VTT method for the study of structure in the Local Supercluster of Galaxies [13]. The 3D VTT method is a geometrical method based only upon the positions of galaxies in space. For a distribution of seed galaxies, the VTT creates convex polygonal volumes each containing a single seed and enclosing the whole area closest to the seed. That is the definition of a Voronoi 418

3 R.A Dec. -60 P' >400 FIGURE 1. Positions of PF galaxy clusters on the celestial sphere. f z FIGURE 2. Histogram for the estimated distances of PF galaxy clusters. cell in 3D. The natural partitioning of space by the VTT has been used to model the large-scale distribution of matter. In the present work the positions of galaxy clusters provide input as seeds for the 3D Voronoi tessellation, and the Voronoi cell around each cluster is interpreted as the effective volume occupied by each cluster in space. The inverse values of the same volume yield local densities for each galaxy position. The FoF method was applied by Turner and Gott [14] and Press and Davis [15]; it combines all input structures with distances to the nearest ones, less than some minimal value. The algorithm, along with the percolation method, began worldwide use following a paper by Huchra and Geller [16]. We calculated distances to the nearest galaxy clusters for each of the 1746 input structures. They fall within the limits 3 to 120 h 1 Mpc with a median value of

4 h 1 Mpc, but only 13 clusters have distances of 50 h 1 Mpc or more. A histogram of distances to the nearest structures for the bulk of the input data is shown in Fig f D (h -1 Mpc) FIGURE 3. Variations in distance to the nearest clusters in the input sample. Possible isolated clusters (D > 70 h 1 Mpc) are not shown. A combination of the two methods described above was motivated by the small number of galaxy clusters in superclusters. Possible poor superclusters can be lost because of their large individual volumes; the FoF method regulates only part of the study, while the VTT method permits us to determine the effective volume and the mean galaxy density of the superclusters. As a result, we have the possibility of finding superclusters as well as an additional 13 isolated galaxy clusters. Finally, isolated galaxy clusters are interpreted as objects with the largest Voronoi cell volumes and/or maximal distances to the nearest cluster. CONCLUSIONS We find that our observational data and selected method of analysis are ideally suited for the creation of a catalogue of galaxy superclusters as well as a list of isolated galaxy clusters. Both will be useful for a future comparison of the properties of galaxy clusters with different environments. ACKNOWLEDGEMENTS This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This research has made use of NASA s Astrophysics Data System. The author thanks Jan Kochanowski University, Kielce, Poland for hospitality and financial support during her stays in Kielce during the preparation of this work. 420

5 REFERENCES 1. G. O. Abell, H. G. Corwin, and R. P. Olowin, ApJS 70, (1989). 2. E. Zucca, G.Zamorani, R. Scaramella, and G. Vettolani, ApJ 407, (1993). 3. M. Einasto, E. Tago, J. Jaaniste, J. Einasto, and H. Andernach, A&AS 123, (1997). 4. J. Einasto, M. Einasto, E. Tago, E. Saar, et al., A&A 462, (2007). 5. M. Einasto, J. Einasto, E. Tago, H. Andernach, et al., AJ 123, (2002). 6. G. B.Dalton, S. J.Maddox, W. J.Sutherland, and G. Efstathiou, MNRAS 289, (1997). 7. E. Panko, and P. Flin, JAD 12, 1-9 (2006). 8. R. Ungruhe, W. C. Seitter, and H. W. J. Duerbeck, JAD 9, 1-12 (2003). 9. M. Ramella, M. Nonino, W. Boschin, and D. Fadda, Cluster Identification via Voronoi Tesselation, in Observational Cosmology: The Development of Galaxy Systems, edited by G. Giuricin, M. Mezzetti, and P. Salucci, ASP Conference Series 176, (1999). 10. M. Ramella, W. Boschin, D. Fadda, and M. Nonino, A&A 368, (2001). 11. E. Panko, and P. Flin, Application of the Voronoi Tessellation Technique for Galaxy Cluster Search in the Munster Red Sky Survey, in Outskirts of Galaxy Clusters: Intense Life in the Suburbs, edited by A. Diaferio, IAU Colloquium 195, (2004). 12. M. Biernacka, P. Flin, T. Juszczyk, and E. Panko, The Properties of Nearby Galaxy Structures, in Cosmology Across Cultures, edited by J. A. Rubino-Martin, J. A. Belmonte, F. Prada, and A. Alberdi, ASP Conference Series 409, (2009). 13. O. V. Melnyk, A. A. Elyiv, and I. B. Vavilova, KFNT 22, (2006). 14. E. Turner, and J. R. Gott, ApJS 32, (1976). 15. W. H. Press, and M. Davis, ApJ 259, (1982). 16. J. P. Huchra, and M. J. Geller, ApJ 257, (1982). 421

arxiv: v1 [astro-ph] 8 Dec 2007

arxiv: v1 [astro-ph] 8 Dec 2007 Kinematika i Fizika Nebesnykh Tel. Vol. 22, No. 4, pp. 283-296 (2006) arxiv:0712.1297v1 [astro-ph] 8 Dec 2007 The Structure of the Local Supercluster of Galaxies Revealed by the Three-Dimensional Voronoi