Extended percolation analysis of the cosmic web

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 $h^{-1}$ Mpc the percolation threshold density for clusters is $\log P_C = 0.718 \pm 0.014$, and for voids is $\log P_V = -0.816 \pm 0.015$, very different from percolation thresholds for random samples, $\log P_0 = 0.00 \pm 0.02$. 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

Dynamical state of superclusters of galaxies: do superclusters expand or have they started to collapse?

We investigate the dynamical state of superclusters in Lambda cold dark matter ($\Lambda$CDM) cosmological models, where the density parameter $\Omega_0=0.2-0.4$ and $\sigma_8$ (the rms fluctuation on the $8h^{-1}$Mpc scale) is $0.7-0.9$. To study the nonlinear regime, we use N-body simulations. We define superclusters as maxima of the density field smoothed on the scale $R=10h^{-1}$Mpc. Smaller superclusters defined by the density field smoothed on the scale $R=5h^{-1}$Mpc are also investigated. We find the relations between the radially averaged peculiar velocity and the density contrast in the superclusters for different cosmological models. These relations can be used to estimate the dynamical state of a supercluster on the basis of its density contrast. In the simulations studied, all the superclusters defined with the $10h^{-1}$Mpc smoothing are expanding by the present epoch. Only a small fraction of the superclusters defined with $R=5h^{-1}$Mpc has already reached their turnaround radius and these superclusters have started to collapse. In the model with $\Omega_0=0.3$ and $\sigma_8=0.9$, the number density of objects which have started to collapse is $5 \times 10^{-6}h^3$Mpc$^{-3}$. The results for superclusters in the N-body simulations are compared with the spherical collapse model. We find that the radial peculiar velocities in N-body simulations are systematically smaller than those predicted by the spherical collapse model ($\sim 25$% for the $R=5h^{-1}$Mpc superclusters).Comment: 10 pages, 8 figures, accepted for publication in MNRA

Evolution of superclusters and supercluster cocoons in various cosmologies

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

The rms peculiar velocity of galaxy clusters for different cluster masses and radii

We investigate the rms peculiar velocity of galaxy clusters in the Lambda cold dark matter ($\Lambda$CDM) and tau cold dark matter ($\tau$CDM) cosmological models using N-body simulations. Cluster velocities for different cluster masses and radii are examined. To identify clusters in the simulations we use two methods: the standard friends-of-friends (FOF) method and the method, where the clusters are defined as the maxima of the density field smoothed on the scale $R\sim 1h^{-1}$ Mpc (DENSMAX). If we use the DENSMAX method, the size of the selected clusters is similar for all clusters. We find that the rms velocity of clusters defined with the DENSMAX method is almost independent of the cluster density and similar to the linear theory expectations. The rms velocity of FOF clusters decreases with the cluster mass and radius. In the $\Lambda$CDM model, the rms peculiar velocity of massive clusters with an intercluster separation $d_{cl}=50h^{-1}$ Mpc is $\approx$15% smaller than the rms velocity of the clusters with a separation $d_{cl}=10h^{-1}$Mpc.Comment: 10 pages, 7 figures, 4 tables, accepted for publication in MNRA

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

We provide flux-limited and volume-limited galaxy group and cluster catalogues, based on the spectroscopic sample of the SDSS data release 10 galaxies. We used a modified friends-of-friends (FoF) 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 588193 galaxies and 82458 groups. The volume-limited catalogues are complete for absolute magnitudes down to M_r = -18.0, -18.5, -19.0, -19.5, -20.0, -20.5, and -21.0; the completeness is achieved within different spatial volumes, respectively. Our analysis shows that flux-limited and volume-limited group samples are well compatible to each other, especially for the larger groups/clusters. Dynamical mass estimates, based on radial velocity dispersions and group extent in the sky, are added to the extracted groups. The catalogues can be accessed via http://cosmodb.to.ee and the Strasbourg Astronomical Data Center (CDS).Comment: 16 pages, 18 figures, 2 tables, accepted for publication in A&

Wavelet analysis of the formation of the cosmic web

According to the modern cosmological paradigm galaxies and galaxy systems form from tiny density perturbations generated during the very early phase of the evolution of the Universe. Using numerical simulations we study the evolution of phases of density perturbations of different scales to understand the formation and evolution of the cosmic web. We apply the wavelet analysis to follow the evolution of high-density regions (clusters and superclusters) of the cosmic web. We show that the positions of maxima and minima of density waves (their spatial phases) almost do not change during the evolution of the structure. Positions of extrema of density perturbations are the more stable, the larger is the wavelength of perturbations. Combining observational and simulation data we conclude that the skeleton of the cosmic web was present already in an early stage of structure evolution.Comment: 12 pages, 8 figures, revised versio

The biasing phenomenon

{We study biasing as a physical phenomenon by analysing geometrical and clustering properties of density fields of matter and galaxies.} {Our goal is to determine the bias function using a combination of geometrical and power spectrum analysis of simulated and real data.} {We apply an algorithm based on local densities of particles, $\delta$, to form simulated biased models using particles with $\delta \ge \delta_0$. We calculate the bias function of model samples as functions of the particle density limit $\delta_0$. We compare the biased models with Sloan Digital Sky Survey (SDSS) luminosity limited samples of galaxies using the extended percolation method. We find density limits $\delta_0$ of biased models, which correspond to luminosity limited SDSS samples.} {Power spectra of biased model samples allow to estimate the bias function $b(>L)$ of galaxies of luminosity $L$. We find the estimated bias parameter of $L_\ast$ galaxies, $b_\ast =1.85 \pm 0.15$. } {The absence of galaxy formation in low-density regions of the Universe is the dominant factor of the biasing phenomenon. Second largest effect is the dependence of the bias function on the luminosity of galaxies. Variations in gravitational and physical processes during the formation and evolution of galaxies have the smallest influence to the bias function. }Comment: 20 pages, 16 figures. Submitted to Astronomy & Astrophysic