Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDynamical state of superclusters of galaxies: do superclusters expand or have they started to collapse?
85
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
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).
rate research
Read More
We study the distribution of galaxies and galaxy clusters in a 10^deg x 6^deg field in the Aquarius region. In addition to 63 clusters in the literature, we have found 39 new candidate clusters using a matched-filter technique and a counts-in-cells analysis. From redshift measurements of galaxies in the direction of these cluster candidates, we present new mean redshifts for 31 previously unobserved clusters, while improved mean redshifts are presented for 35 other systems. About 45% of the projected density enhancements are due to the superposition of clusters and/or groups of galaxies along the line of sight, but we could confirm for 72% of the cases that the candidates are real physical associations similar to the ones classified as rich galaxy clusters. On the other hand, the contamination due to galaxies not belonging to any concentration or located only in small groups along the line of sight is ~ 10%. Using a percolation radius of 10 h^{-1} Mpc (spatial density contrast of about 10), we detect two superclusters of galaxies in Aquarius, at z = 0.086 and at z = 0.112, respectively with 5 and 14 clusters. The latter supercluster may represent a space overdensity of about 160 times the average cluster density as measured from the Abell et al. (1989) cluster catalog, and is possibly connected to a 40 h^{-1} Mpc filament from z ~ 0.11 to 0.14.
We investigate a spatially-flat cold dark matter model (with the matter density parameter $Omega_m=0.3$) with a primordial feature in the initial power spectrum. We assume that there is a bump in the power spectrum of density fluctuations at wavelengths $lambda sim 30-60h^{-1}$Mpc, which correspond to the scale of superclusters of galaxies. There are indications for such a feature in the power spectra derived from redshift surveys and also in the power spectra derived from peculiar velocities of galaxies. We study the mass function of clusters of galaxies, the power spectrum of the CMB temperature fluctuations, the rms bulk velocity and the rms peculiar velocity of clusters of galaxies. The baryon density is assumed to be consistent with the BBN value. We show that with an appropriately chosen feature in the power spectrum of density fluctuations at the scale of superclusters, the mass function of clusters, the CMB power spectrum and peculiar velocities are in good agreement with the observed data.
We perform an exhaustive comparison among central galaxies from SDSS catalogs in different local environments at 0.01<=z<=0.08. The central galaxies are separated into two categories: group centrals (host halos containing satellites) and field centrals (host halos without satellites). From the latter, we select other two subsamples: isolated centrals and bright field centrals, both with the same magnitude limit. The stellar mass (Ms) distributions of the field and group central galaxies are different, which explains why in general the field central galaxies are mainly located in the blue cloud/star forming regions, whereas the group central galaxies are strongly biased to the red sequence/passive regions. The isolated centrals occupy the same regions as the bright field centrals since both populations have similar Ms distributions. At parity of Ms, the color and specific star formation rate (sSFR) distributions of the samples are similar, specially between field and group centrals. Furthermore, we find that the stellar-to-halo mass (Ms-Mh) relation of isolated galaxies does not depend on the color, sSFR and morphological type. For systems without satellites, the Ms-Mh relation steepens at high halo masses compared to group centrals, which is a consequence of assuming a one-to-one relation between group total stellar mass and halo mass. Under the same assumption, the scatter around the Ms-Mh relation of centrals with satellites increases with halo mass. Our results suggest that the mass growth of central galaxies is mostly driven by the halo mass, with environment and mergers playing a secondary role.
The Large-Scale Structure (LSS) of the Universe is a homogeneous network of galaxies separated in dense complexes, the superclusters of galaxies, and almost empty voids. The superclusters are young structures that did not have time to evolve into dynamically relaxed systems through the age of the Universe. Internally, they are very irregular, with dense cores, filaments and peripheral systems of galaxies. We propose a methodology to map the internal structure of superclusters of galaxies using pattern recognition techniques. Our approach allows to: i) identify groups and clusters in the LSS distribution of galaxies; ii) correct for the fingers of God projection effect, caused by the partial knowledge of the third space coordinate; iii) detect filaments of galaxies and trace their skeletons. In this paper, we present the algorithms, discuss the optimization of the free parameters and evaluate the results of its application. With this methodology, we have mapped the internal structure of 42 superclusters in the nearby universe (up to $z=0.15$).
We present a morphological study of the two richest superclusters from the 2dF Galaxy Redshift Survey (SCL126, the Sloan Great Wall, and SCL9, the Sculptor supercluster). We use Minkowski functionals, shapefinders, and galaxy group information to study the substructure of these superclusters as formed by different populations of galaxies. We compare the properties of grouped and isolated galaxies in the core region and in the outskirts of superclusters. The fourth Minkowski functional $V_3$ and the morphological signature $K_1$- $K_2$ show a crossover from low-density morphology (outskirts of supercluster) to high-density morphology (core of supercluster) at mass fraction $m_f approx 0.7$. The galaxy content and the morphology of the galaxy populations in supercluster cores and outskirts is different. The core regions contain a larger fraction of early type, red galaxies, and richer groups than the outskirts of superclusters. In the core and outskirt regions the fine structure of the two prominent superclusters as delineated by galaxies from different populations also differs. Our results suggest that both local (group/cluster) and global (supercluster) environments are important in forming galaxy morphologies and colors (and determining the star formation activity). The differences between the superclusters indicate that these superclusters have different evolutional histories (Abridged).
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
