Cosmological probes based on galaxy clusters rely on cluster number counts and large-scale structure information. X-ray cluster surveys are well suited for this purpose, since they are far less affected than optical surveys by projection effects, and
cluster properties can be predicted with good accuracy. The XMM Cluster Archive Super Survey, X-CLASS, is a serendipitous search of X-ray-detected galaxy clusters in 4176 XMM-Newton archival observations until August 2015. All observations are clipped to exposure times of 10 and 20 ks to obtain uniformity and they span ~269 deg$^2$ across the high-Galactic latitude sky ($|b|> 20^o$). The main goal of the survey is the compilation of a well-selected cluster sample suitable for cosmological analyses. We describe the detection algorithm, the visual inspection, the verification process and the redshift validation of the cluster sample, as well as the cluster selection function computed by simulations. We also present the various metadata that are released with the catalogue, along with the redshifts of 124 clusters obtained with a dedicated multi-object spectroscopic follow-up programme. With this publication we release the new X-CLASS catalogue of 1646 well-selected X-ray-detected clusters over a wide sky area, along with their selection function. The sample spans a wide redshift range, from the local Universe up to z~1.5, with 982 spectroscopically confirmed clusters, and over 70 clusters above z=0.8. Because of its homogeneous selection and thorough verification, the cluster sample can be used for cosmological analyses, but also as a test-bed for the upcoming eROSITA observations and other current and future large-area cluster surveys. It is the first time that such a catalogue is made available to the community via an interactive database which gives access to a wealth of supplementary information, images, and data.
Data from the SPectroscopic IDentification of ERosita Sources (SPIDERS) are searched for a detection of the gravitational redshifting of light from $sim!20,000$ galaxies in $sim!2500$ galaxy clusters using three definitions of the cluster centre: its
Brightest Cluster Galaxy (BCG), the redMaPPer identified Central Galaxy (CG), or the peak of X-ray emission. Distributions of velocity offsets between galaxies and their host clusters centre, found using observed redshifts, are created. The quantity $hat{Delta}$, the average of the radial velocity difference between the cluster members and the cluster systemic velocity, reveals information on the size of a combination of effects on the observed redshift, dominated by gravitational redshifting. The change of $hat{Delta}$ with radial distance is predicted for SPIDERS galaxies in General Relativity (GR), and $f(R)$ gravity, and compared to the observations. The values of $hat{Delta}=-13.5pm4.7$ km s$^{-1}$, $hat{Delta}=-12.5pm5.1$ km s$^{-1}$, and $hat{Delta}=-18.6pm4.8$ km s$^{-1}$ for the BCG, X-ray and CG cases respectively broadly agree with the literature. There is no significant preference of one gravity theory over another, but all cases give a clear detection ($>2.5sigma$) of $hat{Delta}$. The BCG centroid is deemed to be the most robust method in this analysis, due to no well defined central redshift when using an X-ray centroid, and CGs identified by redMaPPer with no associated spectroscopic redshift. For future gravitational redshift studies, an order of magnitude more galaxies, $sim!500,000$, will be required-a possible feat with the forthcoming Vera C. Rubin Observatory, Euclid and eROSITA.
SPIDERS is the spectroscopic follow-up effort of the Sloan Digital Sky Survey IV (SDSS-IV) project for the identification of X-ray selected galaxy clusters. We present our catalogue of 2740 visually inspected galaxy clusters as a part of the SDSS Dat
a Release 16 (DR16). Here we detail the target selection, our methods for validation of the candidate clusters, performance of the survey, the construction of the final sample, and a full description of what is found in the catalogue. Of the sample, the median number of members per cluster is approximately 10, with 818 having 15 or greater. We find that we are capable of validating over 99% of clusters when 5 redshifts are obtained below $z<0.3$ and when 9 redshifts are obtained above $z>0.3$. We discuss the improvements of this catalogues identification of cluster using 33,340 redshifts, with $Delta z_{rm{phot}} / Delta z_{rm{spec}} sim 100$, over other photometric and spectroscopic surveys, as well as present an update to previous ($sigma - L_{X}$) and ($sigma - lambda$) relations. Finally, we present our cosmological constraints derived using the velocity dispersion function.
SPIDERS (The SPectroscopic IDentification of eROSITA Sources) is a large spectroscopic programme for X-ray selected galaxy clusters as part of the Sloan Digital Sky Survey-IV (SDSS-IV). We describe the final dataset in the context of SDSS Data Releas
e 16 (DR16): the survey overall characteristics, final targeting strategies, achieved completeness and spectral quality, with special emphasis on its use as a galaxy cluster sample for cosmology applications. SPIDERS now consists of about 27,000 new optical spectra of galaxies selected within 4,000 photometric red sequences, each associated with an X-ray source. The excellent spectrograph efficiency and a robust analysis pipeline yield a spectroscopic redshift measurement success rate exceeding 98%, with a median velocity accuracy of 20 km s$^{-1}$ (at $z=0.2$). Using the catalogue of 2,740 X-ray galaxy clusters confirmed with DR16 spectroscopy, we reveal the three-dimensional map of the galaxy cluster distribution in the observable Universe up to $zsim0.6$. We highlight the homogeneity of the member galaxy spectra among distinct regions of the galaxy cluster phase space. Aided by accurate spectroscopic redshifts and by a model of the sample selection effects, we compute the galaxy cluster X-ray luminosity function and we present its lack of evolution up to $z=0.6$. Finally we discuss the prospects of forthcoming large multiplexed spectroscopic programmes dedicated to follow up the next generation of all-sky X-ray source catalogues.
Large area catalogs of galaxy clusters constructed from ROSAT All Sky Survey provide the base for our knowledge on the population of clusters thanks to the long-term multiwavelength efforts on their follow-up. Advent of large area photometric surveys
superseding in depth previous all-sky data allows us to revisit the construction of X-ray cluster catalogs, extending the study to lower cluster masses and to higher redshifts and to provide the modelling of the selection function. We perform a wavelet detection of X-ray sources and make extensive simulations of the detection of clusters in the RASS data. We assign an optical richness to each of the 24,788 detected X-ray sources in the 10,382 square degrees of SDSS BOSS area, using redMaPPer version 5.2. We name this survey COnstrain Dark Energy with X-ray (CODEX) clusters. We show that there is no obvious separation of sources on galaxy clusters and AGN, based on distribution of systems on their richness. This is a combination of increasing number of galaxy groups and their selection as identification of an X-ray sources either by chance or due to groups hosting an AGN. To clean the sample, we use a cut on the optical richness at the level corresponding to the 10% completeness of the survey and include it into the modelling of cluster selection function. We present the X-ray catalog extending to a redshift of 0.6 down to X-ray fluxes of $10^{-13}$ ergs s$^{-1}$ cm$^{-2}$. We provide the modelling of the sample selection and discuss the redshift evolution of the high end of the X-ray luminosity function (XLF). Our results on $z<0.3$ XLF are in agreement with previous studies, while we provide new constraints on the $0.3<z<0.6$ XLF. We find a lack of strong redshift evolution of the XLF, provide exact modeling of the effect of low number statistics and AGN contamination and present the resulting constraints on the flat $Lambda$CDM.
X-ray observations of the hot gas filling the intra-cluster medium provide a wealth of information on the dynamics of clusters of galaxies. The global equilibrium of the ICM is believed to be partially ensured by non-thermal pressure support, notably
the dissipation of energy through turbulent motions. Accurate mapping of turbulence using X-ray emission lines is challenging due to the lack of spatially-resolved spectroscopy. Only future instruments such as the X-ray Integral Field Unit (X-IFU) on Athena will have the spatial and spectral resolution to quantitatively investigate the ICM turbulence at all scales. Powerful diagnostics for these studies are line shift and the line broadening maps, and the second-order structure function. When estimating these quantities, instruments will be limited by uncertainties of their measurements, and by the sample variance (aka cosmic variance) of the observation. We extend here the formalism started in our companion paper I to include the effect of statistical uncertainties in the estimation of these line diagnostics, in particular for structure functions. We demonstrate that statistics contribute to the total variance through different terms, which depend on the geometry of the detector, the spatial binning and the nature of the turbulent field. These terms are important when probing the small scales of the turbulence. An application of these equations is performed for the X-IFU, using synthetic turbulent velocity maps of a Coma-like cluster of galaxies. Results are in excellent agreement with the formulas both for the structure function estimation (<3%) and its variance (<10%). The expressions derived here and in paper I are generic, and ensure an estimation of the total errors in any X-ray measurement of turbulent structure functions. They also open the way for optimisations in the upcoming instrumentation and in observational strategies.
X-ray observations of galaxy clusters provide insights on the nature of gaseous turbulent motions, their physical scales and on the fundamental processes they are related to. Spatially-resolved, high-resolution spectral measurements of X-ray emission
lines provide diagnostics on the nature of turbulent motions in emitting atmospheres. Since they are acting on scales comparable to the size of the objects, the uncertainty on these physical parameters is limited by the number of observational measurements, through sample variance. We propose a different and complementary approach for the computation of sample variance to repeating numerical simulations (i.e. Monte-Carlo sampling) by introducing new analytical developments for lines diagnosis. We consider the model of a turbulent gas cloud, consisting in isotropic and uniform turbulence described by a universal Kolmogorov power-spectrum with random amplitudes and phases in an optically thin medium. Following a simple prescription for the 4-term correlation of Fourier coefficients, we derive generic expressions for the sample mean and variance of line centroid shift, line broadening and projected velocity structure function. We perform a numerical validation based on Monte-Carlo simulations for two popular models of gas emissivity based on the beta-model. Generic expressions for the sample variance of line centroid shifts and broadening in arbitrary apertures are derived and match the simulations within their range of applicability. Generic expressions for the mean and variance of the structure function are provided and verified against simulations. An application to the Athena/X-IFU and XRISM/Resolve instruments forecasts the potential of sensitive, spatially-resolved spectroscopy to probe the inertial range of turbulent velocity cascades in a Coma-like galaxy cluster.
Studies of galaxy clusters provide stringent constraints on models of structure formation. Provided that selection effects are under control, large X-ray surveys are well suited to derive cosmological parameters, in particular those governing the dar
k energy equation of state. We forecast the capabilities of the all-sky eROSITA (the extended ROentgen Survey with an Imaging Telescope Array) survey to be achieved by the early 2020s. We bring special attention to modeling the entire chain from photon emission to source detection and cataloguing. The selection function of galaxy clusters for the upcoming eROSITA mission is investigated by means of extensive and dedicated Monte-Carlo simulations. Employing a combination of accurate instrument characterization and of state-of-the-art source detection technique, we determine a cluster detection efficiency based on the cluster fluxes and sizes. Using this eROSITA cluster selection function, we find that eROSITA will detect a total of $sim 10^5$ clusters in the extra-galactic sky. This number of clusters will allow eROSITA to put stringent constraints on cosmological models. We show that incomplete assumptions on selection effects, such as neglecting the distribution of cluster sizes, induce a bias in the derived value of cosmological parameters. Synthetic simulations of the eROSITA sky capture the essential characteristics impacting the next-generation galaxy cluster surveys and they highlight parameters requiring tight monitoring in order to avoid biases in cosmological analyses.
The eROSITA mission will provide the largest sample of galaxy clusters detected in X-ray to date (one hundred thousand expected). This sample will be used to constrain cosmological models by measuring cluster masses. An important mass proxy is the el
ectron temperature of the hot plasma detected in X-rays. We want to understand the detection properties and possible bias in temperatures due to unresolved substructures in the cluster halos. We simulated a large number of galaxy cluster spectra with known temperature substructures and compared the results from analysing eROSITA simulated observations to earlier results from Chandra. We were able to constrain a bias in cluster temperatures and its impact on cluster masses as well as cosmological parameters derived from the survey. We found temperatures in the eROSITA survey to be biased low by about five per cent due to unresolved temperature substructures (compared to emission-weighted average temperatures from the Chandra maps). This bias would have a significant impact on the eROSITA cosmology constraints if not accounted for in the calibration. We isolated the bias effect that substructures in galaxy clusters have on temperature measurements and their impact on derived cosmological parameters in the eROSITA cluster survey.
Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the di
stribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. Aims. This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of $3times 10^{-14},mathrm{erg ,s^{-1}cm^{-2}}$ on the source flux within a 1$^{prime}$ aperture. Methods. The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results. The bright cluster sample consists of systems with masses between $M_{500}=7times 10^{13}$ and $3times 10^{14} M_odot$, mostly located between $z=0.1$ and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the predictions from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of $sigma_8$ and/or $Omega_m$ appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to $zsim1$. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters.
