Galaxy morphology, luminosity, and environment in the SDSS DR7

Tempel, Elmo; Saar, E.; Liivamägi, L. J.; Tamm, A.; Einasto, J.; Einasto, M.; Müller, V.

doi:10.1051/0004-6361/201016196

Cited by 102 publications

(146 citation statements)

References 83 publications

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“…For each galaxy, we have estimated the galaxy morphology as described in Tempel et al (2011). In Tempel et al (2012) the morphologies were compared with those provided by Huertas-Company et al (2011), and a very good agreement was found.…”

Section: Group and Galaxy Propertiesmentioning

confidence: 99%

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Flux- and volume-limited groups/clusters for the SDSS galaxies: catalogues and mass estimation

Tempel

Tamm

Gramann

et al. 2014

A&A

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222

488

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We provide flux-and volume-limited galaxy group and cluster catalogues based on the spectroscopic sample of the galaxies of SDSS data release 10. We used a modified friends-of-friends method with a variable linking length in the transverse and radial directions to identify as many realistic groups as possible. The flux-limited catalogue incorporates galaxies down to m r = 17.77 mag. It includes 588 193 galaxies and 82 458 groups. The volume-limited catalogues are complete for absolute magnitudes down to M r,lim = −18.0, −18.5, −19.0, −19.5, −20.0, −20.5, and −21.0; the completeness is achieved within different spatial volumes. Our analysis shows that flux-and volume-limited group samples are well compatible, especially for the larger groups/clusters. Dynamical mass estimates based on radial velocity dispersions and group extent in the sky were added to the extracted groups.

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Section: Group and Galaxy Propertiesmentioning

confidence: 99%

“…Figure 6 shows the luminosity function in the r-filter for our final sample of the SDSS galaxies. It was calculated using an adaptive smoothing kernel as described in Tempel et al (2011). The vertical lines mark the limits for the different volumelimited samples described above.…”

Section: Group and Galaxy Propertiesmentioning

confidence: 99%

Flux- and volume-limited groups/clusters for the SDSS galaxies: catalogues and mass estimation

Tempel

Tamm

Gramann

et al. 2014

A&A

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222

488

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“…This makes them ideal laboratories to study processes that affect the evolution of galaxies, groups, and clusters of galaxies. A number of studies have already shown that the supercluster environment affects the properties of galaxies, groups, and clusters located there (Einasto et al 2003b;Plionis 2004;Wolf et al 2005;Haines et al 2006;Einasto et al 2007c;Porter et al 2008;Tempel et al 2009;Fleenor & Johnston-Hollitt 2010;Tempel et al 2011;Einasto et al 2011). Other evidence about the influence of the largescale environment of galaxies on their properties comes from the study of the properties of galaxies in void walls (Ceccarelli et al 2008) and from the study of the large-scale environment of quasars (Lietzen et al 2009).…”

Section: Introductionmentioning

confidence: 99%

“…The calculation of luminosities is described in Appendix A (details of this calculation are given also in Tempel et al 2011).…”

Section: Datamentioning

confidence: 99%

SDSS DR7 superclusters

Einasto

Liivamägi

Tago

et al. 2011

A&A

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122

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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 V 3 , the morphological signature (the curve in the shapefinder's K 1 -K 2 plane) and the shape parameter (the ratio of the shapefinders K 1 /K 2 ). 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.

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“…For example, rich superclusters contain high-density cores that may contain merging X-ray clusters and may be collapsing (Small et al 1998;Bardelli et al 2000;Einasto et al 2001;Rose et al 2002;Einasto et al 2007cEinasto et al , 2008. A supercluster environment with a wide range of densities affects the properties of galaxies, groups, and clusters located there (Einasto et al 2003b;Plionis 2004;Wolf et al 2005;Haines et al 2006;Einasto et al 2007d;Porter et al 2008;Tempel et al 2009;Fleenor & Johnston-Hollitt 2010;Tempel et al 2011;Einasto et al 2011b). Einasto et al (2011b) showed that the dynamical evolution of one of the richest superclusters in the Sloan Great Wall (SCL 111, SCl 024 in L10 catalogue) is almost finished, while the richest member of the Wall, SCl 126 (SCl 061) is still dynamically active.…”

Section: Discussionmentioning

confidence: 99%

Principal Component Analysis

Næs

Brockhoff

Tomić

2010

Statistics for Sensory and Consumer Science

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Context. The study of superclusters of galaxies helps us to understand the formation, evolution, and present-day properties of the large-scale structure of the Universe. Aims. We use data about superclusters drawn from the SDSS DR7 to analyse possible selection effects in the supercluster catalogue, to study the physical and morphological properties of superclusters, to find their possible subsets, and to determine scaling relations for our superclusters. Methods. We apply principal component analysis and Spearman's correlation test to study the properties of superclusters. Results. We have found that the parameters of superclusters do not correlate with their distance. The correlations between the physical and morphological properties of superclusters are strong. Superclusters can be divided into two populations according to their total luminosity: high-luminosity ones with L g > 400 10 10 h −2 L ⊙ , and low-luminosity systems. High-luminosity superclusters form two sets, which are more elongated systems with the shape parameter K 1 /K 2 < 0.5 and less elongated ones with K 1 /K 2 > 0.5. The first two principal components account for more than 90% of the variance in the supercluster parameters. We use principal component analysis to derive scaling relations for superclusters, in which we combine the physical and morphological parameters of superclusters. Conclusions. The first two principal components define the fundamental plane, which characterises the physical and morphological properties of superclusters. Structure formation simulations for different cosmologies, and more data about the local and high redshift superclusters are needed to understand the evolution and the properties of superclusters better.

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Galaxy morphology, luminosity, and environment in the SDSS DR7

Cited by 102 publications

References 83 publications

Flux- and volume-limited groups/clusters for the SDSS galaxies: catalogues and mass estimation

Flux- and volume-limited groups/clusters for the SDSS galaxies: catalogues and mass estimation

SDSS DR7 superclusters

Principal Component Analysis

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