506 research outputs found

    Extended percolation analysis of the cosmic web

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    Aims. We develop an extended percolation method to allow the comparison of geometrical properties of the real cosmic web with the simulated dark matter web for an ensemble of over- and under-density systems. Methods. We scan density fields of dark matter (DM) model and SDSS observational samples, and find connected over- and underdensity regions in a large range of threshold densities. Lengths, filling factors and numbers of largest clusters and voids as functions of the threshold density are used as percolation functions. Results. We find that percolation functions of DM models of different box sizes are very similar to each other. This stability suggests that properties of the cosmic web, as found in the present paper, can be applied to the cosmic web as a whole. Percolation functions depend strongly on the smoothing length. At smoothing length 1 h−1h^{-1} Mpc the percolation threshold density for clusters is log⁥PC=0.718±0.014\log P_C = 0.718 \pm 0.014, and for voids is log⁥PV=−0.816±0.015\log P_V = -0.816 \pm 0.015, very different from percolation thresholds for random samples, log⁥P0=0.00±0.02\log P_0 = 0.00 \pm 0.02. Conclusions. The extended percolation analysis is a versatile method to study various geometrical properties of the cosmic web in a wide range of parameters. Percolation functions of the SDSS sample are very different from percolation functions of DM model samples. The SDSS sample has only one large percolating void which fills almost the whole volume. The SDSS sample contains numerous small isolated clusters at low threshold densities, instead of one single percolating DM cluster. These differences are due to the tenuous dark matter web, present in model samples, but absent in real observational samples.Comment: 15 pages, 10 figures, Astronomy & Astrophysics (accepted

    Environmental Enhancement of DM Haloes

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    We study the properties of dark matter haloes of a LCDM model in different environments. Using the distance of the 5th nearest neighbour as an environmental density indicator, we show that haloes in a high density environment are more massive, richer, have larger radii and larger velocity dispersions than haloes in a low density environment. Haloes in high density regions move with larger velocities, and are more spherical than haloes in low density regions. In addition, low mass haloes in the vicinity of the most massive haloes are themselves more massive, larger, and have larger rms velocities and larger 3D velocities than low mass haloes far from massive haloes. The velocities of low mass haloes near massive haloes increase with the parent halo mass. Our results are in agreement with recent findings about environmental effects for groups and clusters of galaxies from deep (SDSS and LCRS) surveys.Comment: 9 pages, 7 figures, submitted for Astronomy and Astrophysic

    Optical and X-ray clusters as tracers of the supercluster-void network. I Superclusters of Abell and X-ray clusters

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    We study the distribution of X-ray selected clusters of galaxies with respect to superclusters determined by Abell clusters of galaxies and show that the distribution of X-ray clusters follows the supercluster-void network determined by Abell clusters. We find that in this network X-ray clusters are more strongly clustered than other clusters. Poor, non-Abell X-ray clusters follow the supercluster-void network as well: these clusters are embedded in superclusters determined by rich clusters and populate filaments between them. We present a new catalog of superclusters of Abell clusters out to a redshift of z_{lim}=0.13, a catalog of X-ray clusters located in superclusters determined by Abell clusters, and a list of additional superclusters of X-ray clusters.Comment: LaTex (sty files added), 16 pages, 3 ps figures, submitted to Astronomical Journal. Animations of the 3D distribution of superclusters of Abell and X-ray clusters at http://www.aai.ee/~maret/SCLVnet.ht

    Superclusters of galaxies from the 2dF redshift survey. I. The catalogue

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    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. 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 Mpc/h. 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.Comment: 16 pages, 11 figures, submitted for Astronomy and Astrophysics. High-resolution pdf file and supplementary data can be found at http://www.aai.ee/~maret/2dfscl.htm

    Steps toward the power spectrum of matter. II. The biasing correction with sigma_8 normalization

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    A new method to determine the bias parameter of galaxies relative to matter is suggested. The method is based on the assumption that gravity is the dominating force which determines the formation of the structure in the Universe. Due to gravitational instability the galaxy formation is a threshold process: in low-density environments galaxies do not form and matter remains in primordial form. We investigate the influence of the presence of void and clustered populations to the power spectrum of matter and galaxies. The power spectrum of galaxies is similar to the power spectrum of matter; the fraction of total matter in the clustered population determines the difference between amplitudes of fluctuations of matter and galaxies, i.e. the bias factor. To determine the fraction of matter in voids and clustered population we perform numerical simulations. The fraction of matter in galaxies at the present epoch is found using a calibration through the sigma_8 parameter.Comment: LaTex (sty files added), 31 pages, 4 PostScript figures embedded, Astrophysical Journal (accepted

    SDSS superclusters: morphology and galaxy content

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    We compare the galaxy populations in superclusters of different morphology in the nearby Universe (180 < d < 270 Mpc) to see whether the inner structure and overall morphology of superclusters are important in shaping galaxy properties in superclusters. Supercluster morphology has been found with Minkowski functionals. We analyse the probability density distributions of colours, morphological types, stellar masses, star formation rates (SFR) of galaxies, and the peculiar velocities of the main galaxies in groups in superclusters of filament and spider types, and in the field. We show that the fraction of red, early-type, low SFR galaxies in filament-type superclusters is higher than in spider-type superclusters; in low-density global environments their fraction is lower than in superclusters. In all environments the fraction of red, high stellar mass, and low SFR galaxies in rich groups is higher than in poor groups. In superclusters of spider morphology red, high SFR galaxies have higher stellar masses than in filament-type superclusters. Groups of equal richness host galaxies with larger stellar masses, a larger fraction of early-type and red galaxies, and a higher fraction of low SFR galaxies, if they are located in superclusters of filament morphology. The peculiar velocities of the main galaxies in groups from superclusters of filament morphology are higher than in those of spider morphology. Groups with higher peculiar velocities of their main galaxies in filament-type superclusters are located in higher density environment than those with low peculiar velocities. There are significant differences between galaxy populations of the individual richest superclusters. Therefore both local (group) and global (supercluster) environments and even supercluster morphology play an important role in the formation and evolution of galaxies.Comment: Comments: 14 pages, 11 figures, accepted for publication in Astronomy and Astrophysic

    Evolution of superclusters and supercluster cocoons in various cosmologies

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    We investigate the evolution of superclusters and supercluster cocoons (basins of attraction), and the influence of cosmological parameters to the evolution. We perform numerical simulations of the evolution of the cosmic web for different cosmological models: the LCDM model with a conventional value of the dark energy (DE) density, the open model OCDM with no DE, the standard SCDM model with no DE, and the Hyper-DE HCDM model with an enhanced DE density value. We find ensembles of superclusters of these models for five evolutionary stages, corresponding to the present epoch z = 0, and to redshifts z = 1, 3, 10, 30. We use diameters of the largest superclusters and the number of superclusters as percolation functions to describe properties of the ensemble of superclusters in the cosmic web. We analyse the size and mass distribution of superclusters in models and in real Sloan Digital Sky Survey (SDSS) based samples. In all models numbers and volumes of supercluster cocoons are independent on cosmological epochs. Supercluster masses increase with time, and geometrical sizes in comoving coordinates decrease with time, for all models. LCDM, OCDM and HCDM models have almost similar percolation parameters. This suggests that the essential parameter, which defines the evolution of superclusters, is the matter density. The DE density influences the growth of the amplitude of density perturbations, and the growth of masses of superclusters, albeit significantly less strongly. The HCDM model has the largest speed of the growth of the amplitude of density fluctuations, and the largest growth of supercluster masses during the evolution. Geometrical diameters and numbers of HCDM superclusters at high threshold densities are larger than for LCDM and OCDM superclusters. SCDM model has about two times more superclusters than other models; SCDM superclusters have smaller diameters and masses.Comment: 14 pages, 10 figures (accepted by Astronomy & Astrophysics). arXiv admin note: text overlap with arXiv:1901.0937
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