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We describe the construction of a suite of galaxy cluster mock catalogues from N-body simulations, based on the properties of the new ROSAT-ESO Flux-Limited X-Ray (REFLEX II) galaxy cluster catalogue. Our procedure is based on the measurements of the cluster abundance, and involves the calibration of the underlying scaling relation linking the mass of dark matter haloes to the cluster X-ray luminosity determined in the emph{ROSAT} energy band $0.1-2.4$ keV. In order to reproduce the observed abundance in the luminosity range probed by the REFLEX II X-ray luminosity function ($0.01<L_{X}/(10^{44}{rm erg},{rm s}^{-1}h^{-2})<10$), a mass-X ray luminosity relation deviating from a simple power law is required. We discuss the dependence of the calibration of this scaling relation on the X-ray luminosity and the definition of halo masses and analyse the one- and two-point statistical properties of the mock catalogues. Our set of mock catalogues provides samples with self-calibrated scaling relations of galaxy clusters together with inherent properties of flux-limited surveys. This makes them a useful tool to explore different systematic effects and statistical methods involved in constraining both astrophysical and cosmological information from present and future galaxy cluster surveys.
This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the RMS errors in log M200c delivered by the different methods (0.18 to 1.08 dex, i.e., a factor of ~1.5 to 12), with abundance matching and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under- or over-estimated by a factor greater than 10. Given the steeply falling high-mass end of the cluster mass function, we recommend that richness or abundance matching-based methods are used in conjunction with these methods as a sanity check for studies selecting high mass clusters. We see a stronger correlation of the recovered to input number of galaxies for both catalogues in comparison with the group/cluster mass, however, this does not guarantee that the correct member galaxies are being selected. We do not observe significantly higher scatter for either mock galaxy catalogues. Our results have implications for cosmological analyses that utilise the masses, richnesses, or abundances of clusters, which have different uncertainties when different methods are used.
Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimisation of analysis methodology and validation of data sets. In this paper, we present a set of 1800 galaxy mock catalogues designed to match the Dark Energy Survey Year-1 BAO sample (Crocce et al. 2017) in abundance, observational volume, redshift distribution and uncertainty, and redshift dependent clustering. The simulated samples were built upon HALOGEN (Avila et al. 2015) halo catalogues, based on a $2LPT$ density field with an exponential bias. For each of them, a lightcone is constructed by the superposition of snapshots in the redshift range $0.45<z<1.4$. Uncertainties introduced by so-called photometric redshifts estimators were modelled with a textit{double-skewed-Gaussian} curve fitted to the data. We also introduce a hybrid HOD-HAM model with two free parameters that are adjusted to achieve a galaxy bias evolution $b(z_{rm ph})$ that matches the data at the 1-$sigma$ level in the range $0.6<z_{rm ph}<1.0$. We further analyse the galaxy mock catalogues and compare their clustering to the data using the angular correlation function $ w(theta)$, the comoving transverse separation clustering $xi_{mu<0.8}(s_{perp})$ and the angular power spectrum $C_ell$.
We study the accuracy of several approximate methods for gravitational dynamics in terms of halo power spectrum multipoles and their estimated covariance matrix. We propagate the differences in covariances into parameter constrains related to growth rate of structure, Alcock-Paczynski distortions and biasing. We consider seven methods in three broad categories: algorithms that solve for halo density evolution deterministically using Lagrangian trajectories (ICE-COLA, Pinocchio and PeakPatch), methods that rely on halo assignment schemes onto dark-matter overdensities calibrated with a target N-body run (Halogen, Patchy) and two standard assumptions about the full density PDF (Gaussian and Lognormal). We benchmark their performance against a set of three hundred N-body simulations, running similar sets of approximate simulations with matched initial conditions, for each method. We find that most methods reproduce the monopole to within $5%$, while residuals for the quadrupole are sometimes larger and scale dependent. The variance of the multipoles is typically reproduced within $10%$. Overall, we find that covariances built from approximate simulations yield errors on model parameters within $10%$ of those from the N-body based covariance.
We utilise mock catalogues from high-accuracy cosmological $N$-body simulations to quantify shifts in the recovery of the acoustic scale that could potentially result from galaxy clustering bias. The relationship between galaxies and dark matter halos presents a complicated source of systematic errors in modern redshift surveys, particularly when aiming to make cosmological measurements to sub-percent precision. Apart from a scalar, linear bias parameter accounting for the density contrast ratio between matter tracers and the true matter distribution, other types of galaxy bias, such as assembly and velocity biases, may also significantly alter clustering signals from small to large scales. We create mocks based on generalised halo occupation populations of 36 periodic boxes from the abacuscosmos release with. In a total volume of $48 , h^{-3} mathrm{Gpc}^3$, we test various biased models along with an unbiased base case. Two reconstruction methods are applied to galaxy samples and the apparent acoustic scale is derived by fitting the two-point correlation function multipoles. With respect to the baseline, we find a $0.3%$ shift in the line-of-sight acoustic scale for one variation in the satellite galaxy population, and we find an $0.7%$ shift for an extreme level of velocity bias of the central galaxies. All other bias models are consistent with zero shift at the $0.2%$ level after reconstruction. We note that the bias models explored are relatively large variations, producing sizeable and likely distinguishable changes in small-scale clustering, the modelling of which would further calibrate the BAO standard ruler.
The mass function of galaxy clusters is a sensitive tracer of the gravitational evolution of the cosmic large-scale structure and serves as an important census of the fraction of matter bound in large structures. We obtain the mass function by fitting the observed cluster X-ray luminosity distribution from the REFLEX galaxy cluster survey to models of cosmological structure formation. We marginalise over uncertainties in the cosmological parameters as well as those of the relevant galaxy cluster scaling relations. The mass function is determined with an uncertainty less than 10% in the mass range 3 x 10^12 to 5 x 10^14 M$_odot$. For the cumulative mass function we find a slope at the low mass end consistent with a value of -1, while the mass rich end cut-off is milder than a Schechter function with an exponential term exp($- M^delta$) with $delta$ smaller than 1. Changing the Hubble parameter in the range $H_0 = 67 - 73 km s^-1 Mpc^{-1}$ or allowing the total neutrino mass to have a value between 0 - 0.4 eV causes variations less than the uncertainties. We estimate the fraction of mass locked up in galaxy clusters: about 4.4% of the matter in the Universe is bound in clusters (inside $r_200$) with a mass larger than 10^14 M$_odot$ and 14% to clusters and groups with a mass larger than 10^13 M$_odot$ at the present Universe. We also discuss the evolution of the galaxy cluster population with redshift. Our results imply that there is hardly any clusters with a mass > 10^15 M$_odot$ above a redshift of z = 1.