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Register a new userThe Velocity Distribution Function of Galaxy Clusters as a Cosmological Probe
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We present a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements. In the standard method, galaxy line-of-sight (LOS) velocities, $v$, or velocity dispersions are used to infer cluster masses, $M$, in order to quantify the halo mass function (HMF), $dn(M)/dlog(M)$, which is strongly affected by mass measurement errors. In our new method, the probability distribution of velocities for each cluster in the sample are summed to create a new statistic called the velocity distribution function (VDF), $dn(v)/dv$. The VDF can be measured more directly and precisely than the HMF and it can also be robustly predicted with cosmological simulations which capture the dynamics of subhalos or galaxies. We apply these two methods to mock cluster catalogs and forecast the bias and constraints on the matter density parameter $Omega_m$ and the amplitude of matter fluctuations $sigma_8$ in flat $Lambda$CDM cosmologies. For an example observation of 200 massive clusters, the VDF with (without) velocity errors constrains the parameter combination $sigma_8Omega_m^{0.29 (0.29)} = 0.587 pm 0.011 (0.583 pm 0.011)$ and shows only minor bias. However, the HMF with dynamical mass errors is biased to low $Omega_m$ and high $sigma_8$ and the fiducial model lies well outside of the forecast constraints, prior to accounting for Eddington bias. When the VDF is combined with constraints from the cosmic microwave background (CMB), the degeneracy between cosmological parameters can be significantly reduced. Upcoming spectroscopic surveys that probe larger volumes and fainter magnitudes will provide a larger number of clusters for applying the VDF as a cosmological probe.
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We study a class of early dark energy (EDE) models, in which, unlike in standard dark energy models, a substantial amount of dark energy exists in the matter-dominated era. We self-consistently include dark energy perturbations, and show that these models may be successfully constrained using future observations of galaxy clusters, in particular the redshift abundance, and the Sunyaev-Zeldovich (SZ) power spectrum. We make predictions for EDE models, as well as LCDM for incoming X-ray (eROSITA) and microwave (South Pole Telescope) observations. We show that galaxy clusters mass function and the SZ power spectrum will put strong constraints both on the equation of state of de today and the redshift at which EDE transits to present-day LCDM like behavior for these models, thus providing complementary information to the geometric probes of dark energy. Not including perturbations in EDE models leads to those models being practically indistinguishable from LCDM. An MCMC analysis of future galaxy cluster surveys provides constraints for EDE parameters that are competitive with and complementary to background expansion observations such as supernovae.
Spherical collapse predicts that a single value of the turnaround density (average matter density within the scale on which a structure detaches from the Hubble flow) characterizes all cosmic structures at the same redshift. It has been recently shown by Korkidis et al. that this feature persists in complex non-spherical galaxy clusters identified in N-body simulations. Here we show that the low-redshift evolution of the turnaround density constrains the cosmological parameters, and that it can be used to derive a local constraint on $Omega_Lambda$ alone, independent of $Omega_m$. The turnaround density thus provides a promising new way to exploit upcoming large cosmological datasets.
We review recent progress in the description of the formation and evolution of galaxy clusters in a cosmological context by using numerical simulations. We focus our presentation on the comparison between simulated and observed X-ray properties, while we will also discuss numerical predictions on properties of the galaxy population in clusters. Many of the salient observed properties of clusters, such as X-ray scaling relations, radial profiles of entropy and density of the intracluster gas, and radial distribution of galaxies are reproduced quite well. In particular, the outer regions of cluster at radii beyond about 10 per cent of the virial radius are quite regular and exhibit scaling with mass remarkably close to that expected in the simplest case in which only the action of gravity determines the evolution of the intra-cluster gas. However, simulations generally fail at reproducing the observed cool-core structure of clusters: simulated clusters generally exhibit a significant excess of gas cooling in their central regions, which causes an overestimate of the star formation and incorrect temperature and entropy profiles. The total baryon fraction in clusters is below the mean universal value, by an amount which depends on the cluster-centric distance and the physics included in the simulations, with interesting tensions between observed stellar and gas fractions in clusters and predictions of simulations. Besides their important implications for the cosmological application of clusters, these puzzles also point towards the important role played by additional physical processes, beyond those already included in the simulations. We review the role played by these processes, along with the difficulty for their implementation, and discuss the outlook for the future progress in numerical modeling of clusters.
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.
We study the systematic bias introduced when selecting the spectroscopic redshifts of brighter cluster galaxies to estimate the velocity dispersion of galaxy clusters from both simulated and observational galaxy catalogues. We select clusters with Ngal > 50 at five low redshift snapshots from a semi-analytic model galaxy catalogue, and from a catalogue of SDSS DR8 groups and clusters across the redshift range 0.021<z<0.098. We employ various selection techniques to explore whether the velocity dispersion bias is simply due to a lack of dynamical information or is the result of an underlying physical process occurring in the cluster, for example, dynamical friction. The velocity dispersions and stacked particle velocity distributions of the parent dark matter (DM) halos are compared to the corresponding cluster dispersions and galaxy velocity distribution. We find a clear bias between the halo and the semi-analytic galaxy cluster velocity dispersion on the order of sigma gal / sigma DM = 0.87-0.95 and a distinct difference in the stacked galaxy and DM particle velocity distribution. We identify a systematic underestimation of the velocity dispersions when imposing increasing absolute I-band magnitude limits. This underestimation is enhanced when using only the brighter cluster members for dynamical analysis on the order of 5-35%, indicating that dynamical friction is a serious source of bias when using galaxy velocities as tracers of the underlying gravitational potential. In contrast to the literature we find that the resulting bias is not only halo mass-dependent but that the nature of the dependence changes according to the galaxy selection strategy. We make a recommendation that, in the realistic case of limited availability of spectral observations, a strictly magnitude-limited sample should be avoided to ensure an unbiased estimate of the velocity dispersion.
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