Several ‘great walls’ are clearly visible in the Durham/UKST Galaxy Redshift Survey (DURS). We make a statistical study of this superlarge-scale structure (SLSS) by applying our core sampling, ...cluster, inertia tensor and minimal-spanning-tree analyses to the DURS. The results in the main support similar results from the complementary Las Campañas Redshift Survey (LCRS); the DURS is a fully three-dimensional, though shallower, survey, whilst the LCRS was carried out in six thin wedges of space. Because of the one-in-three sparse sampling used for DURS, the galaxy filaments of large-scale structure (LSS) are less clear here; the mean separation of ∼25 h−1 Mpc for the richer filaments is consistent with the LCRS result, but the poorer filaments are not seen in the DURS. In contrast, the analysis clearly picks out SLSS and we find, as with the LCRS, that ∼50 per cent of the galaxies lie within the SLSS in regions with overdensities of 5-10 times the mean galaxy density. It quantitatively demonstrates that SLSS is a major component of large-scale structure in the Universe. The SLSS is also confirmed as having statistical parameters similar to those for a sheet-like object, albeit a very irregular one with a highly inhomogeneous inner structure. The ‘mean-free path’, or average separation between SLSS structures, is found to be Ds≈50 h−1 Mpc. The inertia tensor analysis gives mean lengths, widths and thicknesses of ∼20-40, 10 and 5 h−1 Mpc, respectively, for the clusters of SLSS. In particular, the largest great wall in the DURS is found to have a length of ∼75 h−1 Mpc. Unlike the LCRS, the cluster mass function for the three-dimensional DURS has a high mass ‘tail’; such a ‘tail’ would constitute a quantitative signature for the presence of great walls. Finally, theoretical considerations would suggest that the results support arguments for the large-scale biasing of galaxies with respect to dark matter.
In this paper we employ a core-sampling analysis to find characteristic scales for the large- and the superlarge-scale structure (LSS and SLSS, respectively) in the Las Campanas Redshift Survey ...(LCRS). With this method, we show that the spatial distribution of galaxies can be roughly characterized as a superposition of three different populations of structural elements: the richest and most stable part is composed of sheet-like elements which can be identified with the SLSS; a system of rich filaments forms the stable part of the LSS; and a system of poor, sparsely populated filaments, lying preferentially in underdense regions, completes the LSS construction. The SLSS incorporates about 60 per cent of the galaxies within the full survey sample, and this value changes little for subsamples constrained by absolute magnitude. Hence, the number density of galaxies is heavily modulated by the SLSS. The spatial distribution of the SLSS elements is approximately Poissonian and is characterized by a mean separation of elements Dsc ≈ (77 ± 9) h−1 Mpc for the full LCRS sample. This value for Dsc depends only weakly on galaxy luminosity. The stable component of the LSS contains about 20 per cent of the galaxies in the full sample, and the spatial distribution of this component can also be approximated as Poissonian. This distribution is characterized for the full LCRS sample by the mean separation of filaments Dfc ≈ (30 ± 2) h−1 Mpc. The poorest and most sparsely populated component of the LSS contains about 20 per cent of the galaxies in the full LCRS sample. The spatial distribution of this component of the structure can also be described as Poissonian and can be characterized by a mean separation of filaments Dfc ≈ (12.9 ± 0.3) h−1 Mpc. The projected proper thickness of the sheets, tpr is ≈ (4–5) h−1 Mpc, much smaller than the separation of the sheets themselves; hence, galaxies tend to be confined to a relatively small fraction of the survey volume. This heavy concentration of galaxies within the sheets of SLSS, however, is not necessarily accompanied by a similar concentration of dark matter.
Igor Dmitrievich Novikov (on his 80th birthday) Bisnovatyi-Kogan, G.S.; Doroshkevich, Andrei G.; Zelenyi, Lev M. ...
Uspehi fiziceskih nauk,
01/2016, Letnik:
186, Številka:
1
Journal Article
We present a detailed study of the evolution of large-scale structure in N-body simulations using both the theory of Doroshkevich et al. (Paper I) and the new ‘core-sampling’ analysis of Buryak, ...Doroshkevich & Fong. The Zel'dovich approximation shows that under gravitational instability, the velocity field of the initial perturbations in the Universe induces a random network structure, traced by the ‘ridges’ of dark matter (DM) Zel'dovich pancakes or sheet-like structures. The approximate analytic solution of Paper I shows that the mean free path or mean separation of DM pancakes is ∼5 h−1 Mpc. Hence this is a characteristic scale of large-scale structure (LSS) as opposed to the ∼ 50–100 h−1 Mpc scale of superlarge-scale structure (SLSS). The ‘modulation’ of the network structure by the gravitational potential produces on SLSS scales DM underdense regions, which are predicted to correspond to the ‘voids’ seen in the observed galaxy distribution. Our aims in this paper are to explore the usefulness of our ‘core-sampling’ analysis for a quantitative ‘empirical’ description of the evolution of structure in N-body simulations, and to test the theory of Paper I by comparing its prediction with the ‘core-sampling measurement’ of the mean free path between DM LSS elements in an N-body simulation. Six simulations in all are used, and ‘measurements’ are made at several different epochs for each simulation. For such DM particle catalogues, we need also to introduce a heuristic model for the mass function of LSS elements in a core sample, involving a new parameter, fsm, the fraction of mass in ‘supermassive’ clumps, which then measures the degree of structure evolution in a simulation. The results show agreement between theory and the ‘core sample’ measured estimates for the characteristic scales of LSS in simulations. In particular, the theory accurately predicts the time dependence of the evolution of these scales. We demonstrate the dependence of the formation and evolution of structure on the computational box size of a simulation, and we discuss the consequences for small box sizes, such as those currently used in the study of galaxy formation. We also discuss the complementary nature of, in particular, the correlation function approach with ‘core-sampling’ and comment on the relationship of the results with observations.
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