Multiscale phenomenology of the cosmic web

Aragón-Calvo, M. A.; Weygaert, Rien van de; Jones, Bernard J. T.

doi:10.1111/j.1365-2966.2010.17263.x

Cited by 244 publications

(299 citation statements)

References 107 publications

(184 reference statements)

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“…We need to study the morphology and galaxy populations of a larger sample of superclusters to find out whether the differences between galaxy populations in superclusters are also related to their different morphology. Aragón-Calvo et al (2010) recently studied the structure and morphologies of elements that define the cosmic web with the Multiscale Morphology Filter and data from ΛCDM simulations. The authors found several typical morphologies for filaments, which they describe as line, grid, star, and complex filaments.…”

Section: Comparison With Other Studiesmentioning

confidence: 99%

“…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). A detailed information on the morphology of superclusters is needed to find out whether that may also be an important environmental factor in shaping the properties of galaxies and groups of galaxies in superclusters (see also Aragón-Calvo et al 2010). Einasto et al (2007d) showed that the morphology of a typical poor supercluster can be described as a "spider" -a system of several filaments growing from one concentration centre (a rich cluster).…”

Section: Introductionmentioning

confidence: 99%

“…Several methods have been proposed to study the cosmic web (Bharadwaj et al 2004;Stoica et al 2010;Aragón-Calvo et al 2010;Sousbie 2011;Sousbie et al 2011, and references therein). One approach is to determine cosmic structures (in our study -superclusters of galaxies) using the density field and to study their morphology with Minkowski functionals and shapefinders (Schmalzing & Buchert 1997;Sathyaprakash et al 1998;Basilakos 2003;Sheth et al 2003;Shandarin et al 2004;Einasto et al 2007d, and references therein).…”

Section: Introductionmentioning

confidence: 99%

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SDSS DR7 superclusters

Einasto

Liivamägi

Tago

et al. 2011

A&A

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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Section: Comparison With Other Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SDSS DR7 superclusters

Einasto

Liivamägi

Tago

et al. 2011

A&A

122

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“…Stoica et al 2010;Bond et al 2010;Aragón-Calvo et al 2010). Many of the algorithms make use of the fact that filaments are the bridges that connect systems of galaxies (Pimbblet et al 2004;Pimbblet 2005;Colberg et al 2005;González & Padilla 2010;Smith et al 2012;Zhang et al 2013;Alpaslan et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Galaxies infalling into groups: filaments versus isotropic infall

Martínez

Muriel

Coenda

2015

Mon. Not. R. Astron. Soc.

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We perform a comparative analysis of the properties of galaxies infalling into groups classifying them accordingly to whether they are: falling along filamentary structures; or they are falling isotropically. For this purpose, we identify filamentary structures connecting massive groups of galaxies in the SDSS. We perform a comparative analysis of some properties of galaxies in filaments, in the isotropic infall region, in the field, and in groups. We study the luminosity functions (LF) and the dependence of the specific star formation rate (SSFR) on stellar mass, galaxy type, and projected distance to the groups that define the filaments. We find that the LF of galaxies in filaments and in the isotropic infalling region are basically indistinguishable between them, with the possible exception of late-type galaxies. On the other hard, regardless of galaxy type, their LFs are clearly different from that of field or group galaxies. Both of them have characteristic absolute magnitudes and faint end slopes in between the field and group values. More significant differences between galaxies in filaments and in the isotropic infall region are observed when we analyse the SSFR. We find that galaxies in filaments have a systematically higher fraction of galaxies with low SSFR as a function of both, stellar mass and distance to the groups, indicating a stronger quenching of the star formation in the filaments compared to both, the isotropic infalling region, and the field. Our results suggest that some physical mechanisms that determine the differences observed between field galaxies and galaxies in systems, affect galaxies even when they are not yet within the systems.

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“…Information about the shapes of the structures found in the datasets is beyond the scope of this work; we refer the interested reader to recent excellent studies by, e.g., Jasche et al (2010), Aragón-Calvo et al (2010) and Sousbie et al (2009).…”

Section: Introductionmentioning

confidence: 99%

Comparison of density estimation methods for astronomical datasets

Ferdosi

Buddelmeijer

Trager

et al. 2011

A&A

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Context. Galaxies are strongly influenced by their environment. Quantifying the galaxy density is a difficult but critical step in studying the properties of galaxies. Aims. We aim to determine differences in density estimation methods and their applicability in astronomical problems. We study the performance of four density estimation techniques: k-nearest neighbors (kNN), adaptive Gaussian kernel density estimation (DEDICA), a special case of adaptive Epanechnikov kernel density estimation (MBE), and the Delaunay tessellation field estimator (DTFE). Methods. The density estimators are applied to six artificial datasets and on three astronomical datasets, the Millennium Simulation and two samples from the Sloan Digital Sky Survey. We compare the performance of the methods in two ways: first, by measuring the integrated squared error and Kullback-Leibler divergence of each of the methods with the parametric densities of the datasets (in case of the artificial datasets); second, by examining the applicability of the densities to study the properties of galaxies in relation to their environment (for the SDSS datasets). Results. The adaptive kernel based methods, especially MBE, perform better than the other methods in terms of calculating the density properly and have stronger predictive power in astronomical use cases. Conclusions. We recommend the modified Breiman estimator as a fast and reliable method to quantify the environment of galaxies.

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Multiscale phenomenology of the cosmic web

Cited by 244 publications

References 107 publications

SDSS DR7 superclusters

SDSS DR7 superclusters

Galaxies infalling into groups: filaments versus isotropic infall

Comparison of density estimation methods for astronomical datasets

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