The X-CLASS−redMaPPer galaxy cluster comparison

Abstract

Context. This paper is the first in a series undertaking a comprehensive correlation analysis between optically selected and X-rayselected cluster catalogues. The rationale of the project is to develop a holistic picture of galaxy clusters utilising optical and X-raycluster-selected catalogues with well-understood selection functions. Aims. Unlike most of the X-ray/optical cluster correlations to date, the present paper focuses on the non-matching objects in either waveband. We investigate how the differences observed between the optical and X-ray catalogues may stem from (1) a shortcoming of the detection algorithms; (2) dispersion in the X-ray/optical scaling relations; or (3) substantial intrinsic differences between the cluster populations probed in the X-ray and optical bands. The aim is to inventory and elucidate these effects in order to account for selection biases in the further determination of X-ray/optical cluster scaling relations. Methods. We correlated the X-CLASS serendipitous cluster catalogue extracted from the XMM archive with the redMaPPer optical cluster catalogue derived from the Sloan Digital Sky Survey (DR8). We performed a detailed and, in large part, interactive analysis of the matching output from the correlation. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters, respectively. X-ray cluster matching rates were analysed as a function of optical richness. In the second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10 −15 erg s −1 cm −2 in the [0.5−2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Results. We find that all rich (λ ≥ 80) clusters are detected in X-rays out to z = 0.6. Below this redshift, the richness threshold for X-ray detection steadily decreases with redshift. Likewise, all X-ray bright clusters are detected by redMaPPer. After correcting for obvious pipeline shortcomings (about 10% of the cases both in optical and X-ray), ∼50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ∼80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centres. The fraction of clusters totally dominated by AGN-type emission appears to be a few percent. Conversely, ∼40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) − part of the non-matches being due to the X-CLASS sample extending further out than redMaPPer (z < 1.5 vs. z < 0.6), but extending the correlation down to a richness of 5 raises the matching rate to ∼65%. Conclusions. This state-of-the-art study involving two well-validated cluster catalogues has shown itself to be complex, and it points to a number of issues inherent to blind c...

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

“…There are about 5000 such clusters within the eBOSS footprint. In addition, ∼300 clusters are identified serendipitously by XMM and also matched to DR9 (XCLASS; Clerc et al 2012;Sadibekova et al 2014). SPIDERS targets cluster galaxies down to i 21 fiber = (Galactic extinction corrected).…”

SPIDERS: the spectroscopic follow-up of X-ray-selected clusters of galaxies in SDSS-IV

“…The two relevant cluster samples are the COnstrain Dark Energy with X-ray clusters (CODEX; Finoguenov et al, in preparation) and the XMM CLuster Archive Super Survey (XCLASS)-RedMapper catalogue (Clerc et al 2012;Sadibekova et al 2014), respectively. Both are based on X-ray detections of galaxy clusters, yet they differ in their characteristics and their construction.…”

Precise clustering and density evolution of redMaPPer galaxy clusters versus MXXL simulation

“…This cluster finder algorithm was designed to process future large photometric surveys like DES and Large Synoptic Survey Telescope (LSST), but it has been already run on the SDSS DR8 photometric and SDSS DR9 spectroscopic data in order to check the possible systematics associated to the algorithm itself, and compare its results with other clusters catalogues, like the SZ Planck cluster catalogue (Rozo et al 2015a), or the X-CLASS X-ray cluster (Sadibekova et al 2014). These analyses led to an updated 5.10 version of the algorithm described in Rozo et al (2015b), which we will augment here with the latest DR12 release that we show below provides a substantial enhancement in the number of the clusters with reliable spectroscopic redshifts.…”