In the construction of an X-ray selected sample of galaxy clusters for cosmological studies, we have assembled a sample of 495 X-ray sources found to show extended X-ray emission in the first processing of the ROSAT All-Sky Survey. The sample covers the celestial region with declination δ ≥ 0 • and galactic latitude |b II | ≥ 20 • and comprises sources with a count rate ≥ 0.06 counts s −1 and a source extent likelihood of 7. In an optical follow-up identification program we find 378 (76%) of these sources to be clusters of galaxies.It was necessary to reanalyse the sources in this sample with a new X-ray source characterization technique to provide more precise values for the X-ray flux and source extent than obtained from the standard processing. This new method, termed growth curve analysis (GCA), has the advantage over previous methods to be robust, easy to model and to integrate into simulations, to provide diagnostic plots for visual inspection, and to make extensive use of the X-ray data. The source parameters obtained assist the source identification and provide more precise X-ray fluxes. This reanalysis is based on data from the more recent second processing of the ROSAT Survey. We present a catalogue of the cluster sources with the X-ray properties obtained as well as a list of the previously flagged extended sources which are found to have a non-cluster counterpart. We discuss the process of source identification from the combination of optical and X-ray data.To investigate the overall completeness of the cluster sample as a function of the X-ray flux limit, we extent the search for X-ray cluster sources to the data of the second processing of the ROSAT Survey for the northern sky region between 9 h and 14 h in right ascension. We include the search for X-ray emission of known clusters as well as a new investigation of extended X-ray sources. In the course of this search we find X-ray emission from additional 85 Abell clusters and 56 very probable cluster candidates among the newly found extended sources. A comparison of the X-ray cluster number counts of the NORAS sample with the REFLEX Cluster Survey results leads to an estimate of the completeness of the NORAS sample of RASS I extended clusters of about 50% at an X-ray flux of F x (0.1 − 2.4keV) = 3 × 10 −12 erg s −1 cm −2 . The estimated completeness achieved by adding the supplementary sample in the study area amounts to about 82% in comparison to REFLEX. The low completeness introduces an uncertainty in the use of the sample for cosmological statistical studies which will be cured with the completion of the continuing Northern ROSAT All-Sky -3 -(NORAS) cluster survey project.

Aims. We present the final public data release of the VLT/ISAAC near-infrared imaging survey in the GOODS-South field. The survey covers an area of 172.5, 159.6 and 173.1 arcmin 2 in the J, H, and K s bands, respectively. For point sources total limiting magnitudes of J = 25.0, H = 24.5, and K s = 24.4 (5σ, AB) are reached within 75% of the survey area. Thus these observations are significantly deeper than the previous EIS Deep Public Survey which covers the same region. The image quality is characterized by a point spread function ranging between 0.34 and 0.65 FWHM. The images are registered to a common astrometric grid defined by the GSC 2 with an accuracy of ∼0.06 RMS over the whole field. The overall photometric accuracy, including all systematic effects, adds up to 0.05 mag. The data are publicly available from the ESO science archive facility. Methods. We describe the data reduction, the calibration, and the quality control process. The final data set is characterized in terms of astrometric and photometric properties, including the PSF and the curve of growth. We establish an empirical model for the sky background noise in order to quantify the variation of limiting depth and statistical photometric errors over the survey area. We define a catalog of K s -selected sources which contains JHK s photometry for 7079 objects. Differential aperture corrections were applied to the color measurements in order to avoid possible biases as a result of the variation of the PSF. We briefly discuss the resulting color distributions in the context of available redshift data. Furthermore, we estimate the completeness fraction and relative contamination due to spurious detections for source catalogs extracted from the survey data. For this purpose, an empirical study based on a deep K s image of the Hubble Ultra Deep Field is combined with extensive image simulations. Results. With respect to previous deep near-infrared surveys, the surface density of faint galaxies has been established with unprecedented accuracy by virtue of the unique combination of depth and area of this survey. We derived galaxy number counts over eight magnitudes in flux up to J = 25.25, H = 25.0, K s = 25.25 (in the AB system). Very similar faint-end logarithmic slopes between 0.24 and 0.27 mag −1 were measured in the three bands. We found no evidence for a significant change in the slope of the logarithmic galaxy number counts at the faint end.

Abstract. We present a measure of the power spectrum on scales from 15 to 800 h −1 Mpc using the ROSAT-ESO Flux-Limited X-Ray (REFLEX) galaxy cluster catalogue. The REFLEX survey provides a sample of the 452 X-ray brightest southern clusters of galaxies with the nominal flux limit S = 3.0 10 −12 erg s −1 cm −2 for the ROSAT energy band (0.1 − 2.4) keV. Several tests are performed showing no significant incompletenesses of the REFLEX clusters with X-ray luminosities brighter than 10 43 erg s −1 up to scales of about 800 h −1 Mpc. They also indicate that cosmic variance might be more important than previous studies suggest. We regard this as a warning not to draw general cosmological conclusions from cluster samples with a size smaller than REFLEX. Power spectra, P (k), of comoving cluster number densities are estimated for flux-and volume-limited subsamples. The most important result is the detection of a broad maximum within the comoving wavenumber range 0.022 ≤ k ≤ 0.030 h Mpc −1 . The data suggest an increase of the power spectral amplitude with X-ray luminosity. Compared to optically selected cluster samples the REFLEX P (k) is flatter for wavenumbers k ≤ 0.05 h Mpc −1 thus shifting the maximum of P (k) to larger scales. The smooth maximum is not consistent with the narrow peak detected at k = 0.05 h Mpc −1 using the Abell/ACO richness ≥0 data. In the range 0.02 ≤ k ≤ 0.4 h Mpc −1 general agreement is found between the slope of the REFLEX P (k) and those obtained with optically selected galaxies. A semi-analytic description of the biased nonlinear power spectrum in redshift space gives the best agreement for low-density Cold Dark Matter models with or without a cosmological constant.

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We determine the Minkowski functionals for a sample of Abell/ACO clusters, 401 with measured and 16 with estimated redshifts. The four Minkowski functionals (including the void probability function and the mean genus) deliver a global description of the spatial distribution of clusters on scales from 10 to 60h −1 Mpc with a clear geometric interpretation. Comparisons with mock catalogues of N-body simulations using different variants of the CDM model demonstrate the discriminative power of the description. The standard CDM model and the model with tilted perturbation spectrum cannot generate the Minkowski functionals of the cluster data, while a model with a cosmological constant and a model with breaking of the scale invariance of perturbations (BSI) yield compatible results.

As the largest, clearly defined building blocks of our Universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterise the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10 −12 erg s −1 cm −2 (0.1 -2.4 keV) increasing the sample size by about a factor of two. The NORAS II cluster survey now reaches the same quality and depth of its counterpart, the Southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z = 0.102. We provide a number of statistical functions including the logN-logS and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ 8 and Ω m , yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems to an all-sky sample, just excluding the Zone-of-Avoidance.

The simulated matter distribution on large scales is studied using core‐sampling, cluster analysis, inertia tensor analysis and minimal spanning tree techniques. Seven simulations in large boxes for five cosmological models with COBE‐normalized CDM‐like power spectra are studied. A wall‐like superlarge‐scale structure with parameters similar to the observed one is found for the OCDM and ΛCDM models with Οmh = 0.2−0.3. In these simulations, the rich structure elements with a typical value for the largest extension of ∼(30 − 50) h−1 Mpc incorporate ∼40 per cent of matter with overdensity of about 10 above the mean. These rich elements are formed by the anisotropic non‐linear compression of sheets with an original size of ∼(15−25) h−1 Mpc. They surround low‐density regions with a typical diameter ∼(50−70) h−1 Mpc. The statistical characteristics of these structures are found to be approximately consistent with observations and theoretical expectations. The cosmological models with higher matter density Ωm=1 in CDM with Harrison–Zeldovich or tilted power spectra cannot reproduce the characteristics of the observed galaxy distribution because of the very strong disruption of the rich structure elements. Another model with a broken scale‐invariant initial power spectrum (BCDM) does not show enough matter concentration in the rich structure elements.

The method of constrained randomization, which was originally developed in the field of time-series analysis for testing for non-linearities, is extended to the case of three-dimensional point distributions as they are typical in the analysis of the large-scale structure of galaxy distributions in the Universe.With this technique it is possible to generate for a given data set so-called surrogate data sets that have the same linear properties as the original data whereas higher order or nonlinear correlations are not preserved. The analysis of the original and surrogate data sets with measures, which are sensitive to non-linearities, yields valuable information about the existence of non-linear correlations in the data. On the other hand one can test whether given statistical measures are able to account for higher order or non-linear correlations by applying them to original and surrogate data sets.We demonstrate how to generate surrogate data sets from a given point distribution, which have the same linear properties (power spectrum) as well as the same density amplitude distribution but different morphological features.We propose weighted scaling indices, which measure the local scaling properties of a point set, as a non-linear statistical measure to quantify local morphological elements in large-scale structure. Using surrogates it is shown that the data sets with the same two-point correlation functions have slightly different void probability functions and especially a different set of weighted scaling indices.Thus a refined analysis of the large-scale structure becomes possible by calculating local scaling properties whereby the method of constrained randomization yields a vital tool for testing the performance of statistical measures in terms of sensitivity to different topological features and discriminative power.