We use the 2dF Galaxy Group Catalogue constructed by Merchán & Zandivarez to study the large-scale structure of the Universe traced by galaxy groups. We concentrate on the computation of the power ...spectrum and the two-point correlation function. The resulting group power spectrum shows a similar shape to the galaxy power spectrum obtained from the 2dF Galaxy Redshift Survey by Percival et al., but with a higher amplitude quantified by a relative bias in redshift space of bs(k) ∼ 1.5 on the range of scales analysed in this work, 0.025 < k/h Mpc−1 < 0.45. The group two-point correlation function for the total sample is well described by a power law with correlation length s0= 8.9 ± 0.3 h−1 Mpc and slope γ=−1.6 ± 0.1 on scales of s < 20 h−1 Mpc. In order to study the dependence of the clustering properties on group mass, we split the catalogue into four subsamples defined by different ranges of group virial masses. Our results are consistent with a 40 per cent increase of the correlation length s0 when the minimum mass of the sample increases from to . These computations allow a fair estimate of the relation described by the correlation length s0 and the mean intergroup separation dc for galaxy systems of low mass. Our results show that an empirical scaling law s0= 4.7d0.32c provides a very good fit to the results from this work, as well as to previous results obtained for groups and clusters of galaxies. The same law describes the predictions for dark matter haloes in N-body simulations of Λ cold dark matter (ΛCDM) models. We also extend our study to the redshift space distortions of galaxy groups, where we find that the anisotropies in the clustering pattern of the 2dF Galaxy Group Catalogue are consistent with gravitational instability, with a flattening of the redshift-space correlation function contours in the direction of the line of sight. The group pairwise velocities found from this analysis for a sample of groups with masses are consistent with 〈w2〉1/2= (280+50−110) km s−1, in agreement with ΛCDM cosmological simulations. The bias factor for the 2dF groups of moderate masses is consistent with the values predicted by the combination of a CDM model and the ellipsoidal collapse model for the formation of structures.
We have analyzed the distribution of galaxies in groups identified in the largest redshift surveys available at present: the final release of the 2dF Galaxy Redshift Survey and the first release of ...the Sloan Digital Sky Survey. Our work comprises the study of the galaxy density profiles and the fraction of galaxies per spectral type as a function of the groupcentric distance. We have calculated the projected galaxy density profiles of galaxy groups using composite samples in order to increase the statistical significance of the results. Special care has been taken in order to avoid possible biases in the group identification and the construction of the projected galaxy density profile estimator. The results show that the projected galaxy density profiles obtained for both redshift surveys are in agreement with a projected Navarro, Frenk, and White prediction in the range 0.15 < r/r sub(200) < 1, whereas a good fit for the measured profiles in the whole range of r/r sub(200) is given by a projected King profile. We have adopted a generalized King profile to fit the measured projected density profiles per spectral type. In order to infer the three-dimensional galaxy density profiles, we deproject the two-dimensional density profiles using a deprojection method similar to that developed by Allen and Fabian. From two-dimensional and three-dimensional galaxy density profiles, we have estimated the corresponding galaxy fractions per spectral type. The two-dimensional fraction of galaxies computed using the projected profiles shows a similar segregation of galaxy spectral types as that obtained by Dominguez and coworkers for groups in the early data release of the 2dF Galaxy Redshift Survey. As expected, the trends obtained for the three-dimensional galaxy fractions show steeper slopes than those observed in the two-dimensional fractions.
We delved into the assembly pathways and environments of compact groups (CGs) of galaxies using mock catalogues generated from semi-analytical models (SAMs) on the Millennium simulation. We ...investigate the ability of SAMs to replicate the observed CG environments and whether CGs with different assembly histories tend to inhabit specific cosmic environments. We also analyse whether the environment or the assembly history is more important in tailoring CG properties. We find that about half of the CGs in SAMs are non-embedded systems, 40% are inhabiting loose groups or nodes of filaments, while the rest distribute evenly in filaments and voids, in agreement with observations. We observe that early-assembled CGs preferentially inhabit large galaxy systems (~ 60%), while around 30% remain non-embedded. Conversely, lately-formed CGs exhibit the opposite trend. We also obtain that lately-formed CGs have lower velocity dispersions and larger crossing times than early-formed CGs, but mainly because they are preferentially non-embedded. Those lately-formed CGs that inhabit large systems do not show the same features. Therefore, the environment plays a strong role in these properties for lately-formed CGs. Early-formed CGs are more evolved, displaying larger velocity dispersions, shorter crossing times, and more dominant first-ranked galaxies, regardless of the environment. Finally, the difference in brightness between the two brightest members of CGs is dependent only on the assembly history and not on the environment. CGs residing in diverse environments have undergone varied assembly processes, making them suitable for studying their evolution and the interplay of nature and nurture on their traits.
Although Compact Groups of galaxies (CGs) have been envisioned as isolated extremely dense structures in the Universe, it is accepted today that many of them could be not as isolated as thought. In ...this work, we study Hickson-like CGs identified in the Sloan Digital Sky Survey Data Release 16 to analyse these systems and their galaxies when embedded in different cosmological structures. To achieve this goal, we identify several cosmological structures where CGs can reside: Nodes of filaments, Loose Groups, Filaments and cosmic Voids. Our results indicate that 45 per cent of CGs do not reside in any of these structures, i.e., they can be considered non-embedded or isolated systems. Most of the embedded CGs are found inhabiting Loose Groups and Nodes, while there are almost no CGs residing well inside cosmic Voids. Some physical properties of CGs vary depending on the environment they inhabit. CGs in Nodes show the largest velocity dispersions, the brightest absolute magnitude of the first-ranked galaxy, and the smallest crossing times, while the opposite occurs in Non-Embedded CGs. When comparing galaxies in all the environments and galaxies in CGs, CGs show the highest fractions of red/early-type galaxy members in most of the absolute magnitudes ranges. The variation between galaxies in CGs inhabiting one or another environment is not as significant as the differences caused by belonging or not to a CG. Our results suggest a plausible scenario for galaxy evolution in CGs in which both, large-scale and local environments play essential roles.
We compute the redshift space power spectrum of two X-ray cluster samples: the X-ray Brightest Abell Cluster Sample (XBACS) and the Brightest Cluster Sample (BCS) using the method developed by ...Feldman, Kaiser & Peacock. The power spectra derived for these samples are in agreement with determinations of other optical and X-ray cluster samples. For XBACS we find the largest power spectrum amplitude expected, given the high richness of this sample (R≥2). In the range 0.05<k<0.4 h Mpc−1 the power spectrum shows a power-law behaviour P(k)∝kn with an index n≃−1.2. In a similar range, 0.04<k<0.3 h Mpc−1, the BCS power spectrum has a smaller amplitude with index n≃−1.0. We do not find significant evidence for a peak at k≃0.05 h Mpc−1, suggesting that claims such of feature detections in some cluster samples could rely on artificial inhomogeneities of the data. We compare our results with power spectrum predictions derived by Moscardini et al. within current cosmological models (LCDM and OCDM). For XBACS we find that both models underestimate the amplitude of the power spectrum but for BCS there is reasonably good agreement at k≳0.03 h Mpc−1 for both models.
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