Optical and X-Ray Clusters as Tracers of the Supercluster-Void Network. I. Superclusters of Abell and X-Ray Clusters

Einasto, M.; Einasto, J.; Tago, E.; Müller, V.; Andernach, H.

doi:10.1086/323707

Cited by 168 publications

(263 citation statements)

References 84 publications

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“…Statistical studies of the galaxy cluster population, in particular the cluster mass function, provide indispensable knowledge of cosmological model parameters (see Allen et al 2011 for a review, Tinker et al 2012), large scale structure (e.g., Bahcall 1988;Einasto et al 2001;Yang et al 2005b;Papovich 2008;Willis et al 2013) and galaxy evolution (e.g., Goto et al 2003;Postman et al 2005;Martínez et al 2008). However, deducing accurate masses of these gravitationally bound structures remains a fundamental challenge for current and future cosmological studies.…”

Section: Introductionmentioning

confidence: 99%

Galaxy Cluster Mass Reconstruction Project – II. Quantifying scatter and bias using contrasting mock catalogues

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Wojtak

Mamon

et al. 2015

Monthly Notices of the Royal Astronomical Society

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This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the RMS errors in log M 200c delivered by the different methods (0.18 to 1.08 dex, i.e., a factor of ∼1.5 to 12), with abundance matching and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under-or over-estimated by a factor greater than 10. Given the steeply falling high-mass end of the cluster mass function, we recommend that richness or abundance matching-based methods are used in conjunction with these methods as a sanity check for studies selecting high mass clusters. We see a stronger correlation of the recovered to input number of galaxies for both catalogues in comparison with the group/cluster mass, however, this does not guarantee that the correct member galaxies are being selected. We do not observe significantly higher scatter for either mock galaxy catalogues. Our results have implications for cosmological analyses that utilise the masses, richnesses, or abundances of clusters, which have different uncertainties when different methods are used.

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Section: Introductionmentioning

confidence: 99%

Galaxy Cluster Mass Reconstruction Project – II. Quantifying scatter and bias using contrasting mock catalogues

Old

Wojtak

Mamon

et al. 2015

Monthly Notices of the Royal Astronomical Society

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“…Oort (1983) gave a review of the early studies of superclusters. Supercluster catalogues compiled based on data A&A 532, A5 (2011) about clusters of galaxies were published by Zucca et al (1993); Einasto et al (1994); Kalinkov & Kuneva (1995); Einasto et al (2001). Recent deep surveys of galaxies (as 2dFGRS and SDSS, see Colless et al 2003;Abazajian et al 2009) introduced a new era in the studies of the large-scale structure of the Universe, where systems of galaxies can be studied in unprecedended detail.…”

Section: Introductionmentioning

confidence: 99%

SDSS DR7 superclusters

Einasto

Liivamägi

Tago

et al. 2011

A&A

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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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“…These studies were based on observational data about galaxies, as well as on data about nearby groups and clusters of galaxies. Classical, relatively deep all-sky supercluster catalogues were constructed using the Abell (1958) and Abell et al (1989) cluster catalogues by Zucca et al (1993), Einasto et al (1994Einasto et al ( , 1997Einasto et al ( , 2001, hereafter E94, E97, E01) and Kalinkov & Kuneva (1995).…”

Section: Introductionmentioning

confidence: 99%

Superclusters of galaxies from the 2dF redshift survey

Einasto¹,

Einasto²,

Tago³

et al. 2006

A&A

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Aims. We use the 2dF Galaxy Redshift Survey data to compile catalogues of superclusters for the Northern and Southern regions of the 2dFGRS, altogether 543 superclusters at redshifts 0.009 ≤ z ≤ 0.2. Methods. We analyse methods of compiling supercluster catalogues and use results of the Millennium Simulation to investigate possible selection effects and errors. We find that the most effective method is the density field method using smoothing with an Epanechnikov kernel of radius 8 h −1 Mpc. Results. We derive positions of the highest luminosity density peaks and find the most luminous cluster in the vicinity of the peak, this cluster is considered as the main cluster and its brightest galaxy the main galaxy of the supercluster. In catalogues we give equatorial coordinates and distances of superclusters as determined by positions of their main clusters. We also calculate the expected total luminosities of the superclusters.

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Optical and X-Ray Clusters as Tracers of the Supercluster-Void Network. I. Superclusters of Abell and X-Ray Clusters

Cited by 168 publications

References 84 publications

Galaxy Cluster Mass Reconstruction Project – II. Quantifying scatter and bias using contrasting mock catalogues

Galaxy Cluster Mass Reconstruction Project – II. Quantifying scatter and bias using contrasting mock catalogues

SDSS DR7 superclusters

Superclusters of galaxies from the 2dF redshift survey

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