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J. Einasto

Publications and source records attributed to J. Einasto.

At least 19 recordsLinked to original sources

The time evolution of bias

We investigate the time evolution of bias of cosmic density fields. We perform numerical simulations of the evolution of the cosmic web for the conventional $Λ$ cold dark matter ($Λ$CDM) model. The simulations cover a wide range of box sizes $L=256 - 1024\Mpc$, and epochs from very early moments $z=30$ to the present moment $z=0$. We calculate spatial correlation functions of galaxies, $ξ(r)$, using dark matter particles of the biased $Λ$CDM simulation. We analyse how these functions describe biasing properties of the evolving cosmic web. We find that for all cosmic epochs the bias parameter, defined through the ratio of correlation functions of selected samples and matter, depends on two factors: the fraction of matter in voids and in the clustered population, and the luminosity (mass) of galaxy samples. Gravity cannot evacuate voids completely, thus there is always some unclustered matter in voids, thus the bias parameter of galaxies is always greater than unity, over the whole range of evolution epochs. We find that for all cosmic epochs bias parameter values form regular sequences, depending on galaxy luminosity (particle density limit), and decreasing with time.

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Correlation functions in 2D and 3D as descriptors of the cosmic web

Aims. Our goal is to find the relation between the two-point correlation functions (CFs) of projected and spatial density fields of galaxies in the context of the cosmic web. Methods. To investigate relations between spatial (3D) and projected (2D) CFs of galaxies we used density fields of two simulations: a $Λ$-dominated cold dark matter (LCDM) model with known particle data, and the Millennium simulation with know data on simulated galaxies. We compare 3D and 2D correlation functions. In the 2D case, we use samples of various thickness to find the dependence of 2D CFs on the thickness of samples. We also compare 3D CFs in real and redshift space. Results. The dominant elements of the cosmic web are clusters and filaments, separated by voids filling most of the volume. In individual 2D sheets, the positions of clusters and filaments do not coincide. As a result, in projection, the clusters and filaments fill in 2D voids. This leads to a decrease in the amplitudes of CFs (and power spectra) in projection. For this reason, the amplitudes of 2D CFs are lower than the amplitudes of 3D correlation functions: the thicker the 2D sample, the greater the difference. Conclusions. Spatial CFs of galaxies contain valuable information about the geometrical properties of the cosmic web that cannot be found from projected CFs.

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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.

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Correlation function: biasing and fractal properties of the cosmic web

We calculated spatial correlation functions of galaxies, $ξ(r)$, structure functions, $g(r)=1 +ξ(r)$, gradient functions, $γ(r)= d \log g(r)/ d \log r$, and fractal dimension functions, $D(r)= 3+γ(r)$, using dark matter particles of the biased $Λ$ cold dark matter (CDM) simulation, observed galaxies of the Sloan Digital Sky Survey (SDSS), and simulated galaxies of the Millennium and EAGLE simulations. We analysed how these functions describe fractal and biasing properties of the cosmic web. The correlation functions of the biased $Λ$CDM model samples at small distances (particle and galaxy separations), $r \le 2.25$~\Mpc, describe the distribution of matter inside dark matter (DM) halos. In real and simulated galaxy samples, only the brightest galaxies in clusters are visible, and the transition from clusters to filaments occurs at a distance $r \approx 0.8 - 1.5$~\Mpc. Real and simulated galaxies of low luminosity, $M_r \ge -19$, have almost identical correlation lengths and amplitudes, indicating that dwarf galaxies are satellites of brighter galaxies, and do not form a smooth population in voids. The combination of several physical processes (e.g. the formation of halos along the caustics of particle trajectories and the phase synchronisation of density perturbations on various scales) transforms the initial random density field to the current highly non-random density field. Galaxy formation is suppressed in voids, which increases the amplitudes of correlation functions and power spectra of galaxies, and increases the large-scale bias parameter. The combined evidence leads to the large-scale bias parameter of $L_\star$ galaxies the value $b_\star =1.85 \pm 0.15$. We find $r_0(L_\star) = 7.20 \pm 0.19$ for the correlation length of $L_\star$ galaxies.

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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, $δ$, to form simulated biased models using particles with $δ\ge δ_0$. We calculate the bias function of model samples as functions of the particle density limit $δ_0$. 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 $δ_0$ 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. }

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Evolution of superclusters in the cosmic web

Aims. We investigate how properties of the ensemble of superclusters in the cosmic web evolve with time. Methods. We perform numerical simulations of the evolution of the cosmic web using the LambdaCDM model in box sizes L0 = 1024, 512, 256 Mpc/h. We find supercluster ensembles of models for four evolutionary stages, corresponding to the present epoch z = 0, and to redshifts z = 1, z = 3, and z = 10. We calculate fitness diameters of superclusters defined from volumes of superclusters divided to filling factors of over-density regions. Geometrical and fitness diameters of largest superclusters, and the number of superclusters as functions of the threshold density are used as percolation functions to describe geometrical properties of the ensemble of superclusters in the cosmic web. We calculate distributions of geometrical and fitness diameters and luminosities of superclusters, and follow time evolution of percolation functions and supercluster distributions. We compare percolation functions and supercluster distributions of models and samples of galaxies of the Sloan Digital Sky Survey (SDSS). Results. Our analysis shows that fitness diameters of superclusters have a minimum at certain threshold density. Fitness diameters around minima almost do not change with time in co-moving coordinates. Numbers of superclusters have maxima which are approximately constant for all evolutionary epochs. Geometrical diameters of superclusters decrease during the evolution of the cosmic web; luminosities of superclusters increase during the evolution. Conclusions. Our study suggests that evolutionary changes occur inside dynamical volumes of superclusters. The stability of fitness diameters and numbers of superclusters during the evolution is an important property of the cosmic web.

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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.

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Shell-like structures in our cosmic neighbourhood

Signatures of the processes in the early Universe are imprinted in the cosmic web. Some of them may define shell-like structures characterised by typical scales. We search for shell-like structures in the distribution of nearby rich clusters of galaxies drawn from the SDSS DR8. We calculate the distance distributions between rich clusters of galaxies, and groups and clusters of various richness, look for the maxima in the distance distributions, and select candidates of shell-like structures. We analyse the space distribution of groups and clusters forming shell walls. We find six possible candidates of shell-like structures, in which galaxy clusters have maxima in the distance distribution to other galaxy groups and clusters at the distance of about 120 Mpc/h. The rich galaxy cluster A1795, the central cluster of the Bootes supercluster, has the highest maximum in the distance distribution of other groups and clusters around them at the distance of about 120 Mpc/h among our rich cluster sample, and another maximum at the distance of about 240 Mpc/h. The structures of galaxy systems causing the maxima at 120 Mpc/h form an almost complete shell of galaxy groups, clusters and superclusters. The richest systems in the nearby universe, the Sloan Great Wall, the Corona Borealis supercluster and the Ursa Major supercluster are among them. The probability that we obtain maxima like this from random distributions is lower than 0.001. Our results confirm that shell-like structures can be found in the distribution of nearby galaxies and their systems. The radii of the possible shells are larger than expected for a BAO shell (approximately 109 Mpc/h versus approximately 120 Mpc/h), and they are determined by very rich galaxy clusters and superclusters with high density contrast while BAO shells are barely seen in the galaxy distribution. We discuss possible consequences of these differences.

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SDSS superclusters: morphology and galaxy content

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.

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Groups in the Millennium Simulation and in SDSS DR7

The Millennium N-body simulation and the Sloan Digital Sky Survey seventh data release (SDSS DR7) galaxy and galaxy group catalogues are compared to study the properties of galaxy groups and the distribution of galaxies in groups. We construct mock galaxy group catalogues for a Millennium semi-analytical galaxy catalogue by using the same friends-of-friends method, which was used by Tago et al to analyse the SDSS data. We analyse in detail the group luminosities, group richnesses, virial radii, sizes of groups and their rms velocities for four volume-limited samples from observations and simulations. Our results show that the spatial densities of groups agree within one order of magnitude in all samples with a rather good agreement between the mock catalogues and observations. All group property distributions have similar shapes and amplitudes for richer groups. For galaxy pairs and small groups, the group properties for observations and simulations are clearly different. In addition, the spatial distribution of galaxies in small groups is different: at the outskirts of the groups the galaxy number distributions do not agree, although the agreement is relatively good in the inner regions. Differences in the distributions are mainly due to the observational limitations in the SDSS sample and to the problems in the semi-analytical methods that produce too compact and luminous groups.

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Multimodality of rich clusters from the SDSS DR8 within the supercluster-void network

We study the relations between the multimodality of galaxy clusters drawn from the SDSS DR8 and the environment where they reside. As cluster environment we consider the global luminosity density field, supercluster membership, and supercluster morphology. We use 3D normal mixture modelling, the Dressler-Shectman test, and the peculiar velocity of cluster main galaxies as signatures of multimodality of clusters. We calculate the luminosity density field to study the environmental densities around clusters, and to find superclusters where clusters reside. We determine the morphology of superclusters with the Minkowski functionals and compare the properties of clusters in superclusters of different morphology. We apply principal component analysis to study the relations between the multimodality parametres of clusters and their environment simultaneously. We find that multimodal clusters reside in higher density environment than unimodal clusters. Clusters in superclusters have higher probability to have substructure than isolated clusters. The superclusters can be divided into two main morphological types, spiders and filaments. Clusters in superclusters of spider morphology have higher probabilities to have substructure and larger peculiar velocities of their main galaxies than clusters in superclusters of filament morphology. The most luminous clusters are located in the high-density cores of rich superclusters. Five of seven most luminous clusters, and five of seven most multimodal clusters reside in spider-type superclusters; four of seven most unimodal clusters reside in filament-type superclusters. Our study shows the importance of the role of superclusters as high density environment which affects the properties of galaxy systems in them.

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Multimodality in galaxy clusters from SDSS DR8: substructure and velocity distribution

We search for the presence of substructure, a non-Gaussian, asymmetrical velocity distribution of galaxies, and large peculiar velocities of the main galaxies in galaxy clusters with at least 50 member galaxies, drawn from the SDSS DR8. We employ a number of 3D, 2D, and 1D tests to analyse the distribution of galaxies in clusters: 3D normal mixture modelling, the Dressler-Shectman test, the Anderson-Darling and Shapiro-Wilk tests and others. We find the peculiar velocities of the main galaxies, and use principal component analysis to characterise our results. More than 80% of the clusters in our sample have substructure according to 3D normal mixture modelling, the Dressler-Shectman (DS) test shows substructure in about 70% of the clusters. The median value of the peculiar velocities of the main galaxies in clusters is 206 km/s (41% of the rms velocity). The velocities of galaxies in more than 20% of the clusters show significant non-Gaussianity. While multidimensional normal mixture modelling is more sensitive than the DS test in resolving substructure in the sky distribution of cluster galaxies, the DS test determines better substructure expressed as tails in the velocity distribution of galaxies. Richer, larger, and more luminous clusters have larger amount of substructure and larger (compared to the rms velocity) peculiar velocities of the main galaxies. Principal component analysis of both the substructure indicators and the physical parameters of clusters shows that galaxy clusters are complicated objects, the properties of which cannot be explained with a small number of parameters or delimited by one single test. The presence of substructure, the non-Gaussian velocity distributions, as well as the large peculiar velocities of the main galaxies, shows that most of the clusters in our sample are dynamically young.

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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.

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Towards understanding the structure of voids in the cosmic web

Our goal is to see how density waves of different scale combine to form voids between galaxy systems of various scale. We perform numerical simulations of structure formation in cubes of size 100 and 256 Mpc/h, with resolutions 256^3 and 512^3 particles and cells. To understand the role of density perturbations of various scale we cut power spectra at scales from 8 to 128 Mpc/h, using in all series identical initial random realisations. We find that small haloes and short filaments form all over the simulation box, if perturbations only up to scale 8 Mpc/h are present. The phenomenon of large multi-scale voids in the cosmic web requires the presence of an extended spectrum of primordial density perturbations. The void phenomenon is due to the action of two processes: the synchronisation of density perturbations of medium and large scales, and the suppression of galaxy formation in low-density regions by the combined action of negative sections of medium- and large-scale density perturbations, so that their densities are less than the mean density, and thus during the evolution their densities decrease.

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The cosmic web for density perturbations of various scales

We follow the evolution of galaxy systems in numerical simulation. Our goal is to understand the role of density perturbations of various scales in the formation and evolution of the cosmic web. We perform numerical simulations with the full power spectrum of perturbations, and with spectrum cut at long wavelengths. Additionally, we have one model, where we cut the intermediate waves. We analyze the density field and study the void sizes and density field clusters in different models. Our analysis shows that the fine structure (groups and clusters of galaxies) is created by small-scale density perturbations of scale $\leq 8$ \Mpc. Filaments of galaxies and clusters are created by perturbations of intermediate scale from $\sim 8$ to $\sim 32$ \Mpc, superclusters of galaxies by larger perturbations. We conclude that the scale of the pattern of the cosmic web is determined by density perturbations of scale up to $\sim 100$ \Mpc. Larger perturbations do not change the pattern of the web, but modulate the richness of galaxy systems, and make voids emptier. The stop of the increase of the scale of the pattern of the cosmic web with increasing scale of density perturbations can probably be explained as the freezing of the web at redshift $z\simeq 0.7$.

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Dark matter

I give a review of the development of the concept of dark matter. The dark matter story passed through several stages from a minor observational puzzle to a major challenge for theory of elementary particles. Modern data suggest that dark matter is the dominant matter component in the Universe, and that it consists of some unknown non-baryonic particles. Properties of dark matter particles determine the structure of the cosmic web.

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SDSS DR7 superclusters. Principal component analysis

We apply the principal component analysis and Spearman's correlation test to study the properties of superclusters drawn from the SDSS DR7. We analyse possible selection effects in the supercluster catalogue, study the physical and morphological properties of superclusters, find their possible subsets, and determine scaling relations for superclusters. We show 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 superclusters form two sets, 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 and define the fundamental plane, which characterises the physical and morphological properties of superclusters. We use principal component analysis to derive scaling relations for superclusters, in which we combine the physical and morphological parameters of superclusters. Structure formation simulations for different cosmologies, and more data about the local and high redshift superclusters are needed to understand better the evolution and the properties of superclusters.

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SDSS DR7 superclusters. Morphology

We study the morphology of a set of superclusters drawn from the SDSS DR7. 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. The morphology of superclusters is described with the fourth Minkowski functional V3, the morphological signature (the curve in the shapefinder's K1-K2 plane) and the shape parameter (the ratio of the shapefinders K1/K2). We investigate the supercluster sample using multidimensional normal mixture modelling, and use Abell clusters to identify our superclusters with known superclusters and to study the large-scale distribution of superclusters. 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. 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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