redMaPPer Clusters Research Articles

Weak lensing measurement of the mass–richness relation of SDSS redMaPPer clusters

We perform a measurement of the mass--richness relation of the redMaPPer galaxy cluster catalogue using weak lensing data from the Sloan Digital Sky Survey. We have carefully characterized a broad range of systematic uncertainties, including shear calibration errors, photo-$z$ biases, dilution by member galaxies, source obscuration, magnification bias, incorrect assumptions about cluster mass profiles, cluster centering, halo triaxiality, and projection effects. We also compare measurements of the lensing signal from two independently-produced shear and photometric redshift catalogues to characterize systematic errors in the lensing signal itself. Using a sample of 5,570 clusters from $0.1\le z\le 0.33$, the normalization of our power-law mass vs.\ $\lambda$ relation is $\log_{10}[M_{200m}/h^{-1}\ M_{\odot}]$ = $14.344 \pm 0.021$ (statistical) $\pm 0.023$ (systematic) at a richness $\lambda=40$, a 7 per cent calibration uncertainty, with a power-law index of $1.33^{+0.09}_{-0.10}$ ($1\sigma$). The detailed systematics characterization in this work renders it the definitive weak lensing mass calibration for SDSS redMaPPer clusters at this time.

THE NEXT GENERATION VIRGO CLUSTER SURVEY. XX. RedGOLD BACKGROUND GALAXY CLUSTER DETECTIONS

ABSTRACT We build a background cluster candidate catalog from the Next Generation Virgo Cluster Survey (NGVS) using our detection algorithm RedGOLD. The NGVS covers 104 deg2 of the Virgo cluster in the -bandpasses to a depth of g ∼ 25.7 mag (5σ). Part of the survey was not covered or has shallow observations in the r band. We build two cluster catalogs: one using all bandpasses, for the fields with deep r-band observations (∼20 deg2), and the other using four bandpasses ( ) for the entire NGVS area. Based on our previous Canada–France–Hawaii Telescope Legacy Survey W1 studies, we estimate that both of our catalogs are ∼100% (∼70%) complete and ∼80% pure, at z ≤ 0.6 (z ≲ 1), for galaxy clusters with masses of M ≳ 1014 M ⊙. We show that when using four bandpasses, though the photometric redshift accuracy is lower, RedGOLD detects massive galaxy clusters up to z ∼ 1 with completeness and purity similar to the five-band case. This is achieved when taking into account the bias in the richness estimation, which is ∼40% lower at 0.5 ≤ z < 0.6 and ∼20% higher at 0.6 < z < 0.8, with respect to the five-band case. RedGOLD recovers all the X-ray clusters in the area with mass M 500 > 1.4 × 1014 M ⊙ and 0.08 < z < 0.5. Because of our different cluster richness limits and the NGVS depth, our catalogs reach lower masses than the published redMaPPer cluster catalog over the area, and we recover ∼90%–100% of its detections.

Tidal stripping as a test of satellite quenching in redMaPPer clusters

When dark matter halos are accreted by massive host clusters, strong gravitational tidal forces begin stripping mass from the accreted subhalos. This stripping eventually removes all mass beyond a subhalo's tidal radius, but the unbound mass remains in the vicinity of the satellite for at least a dynamical time t_dyn. The N-body subhalo study of Chamberlain et al. verified this picture and pointed out a useful observational consequence: measurements of subhalo correlations beyond the tidal radius are sensitive to the infall time, t_infall, of the subhalo onto its host. We perform this cross-correlation measurement using ~ 160,000 red satellite galaxies in SDSS redMaPPer clusters and find evidence that subhalo correlations do persist well beyond the tidal radius, suggesting that many of the observed satellites fell into their current host less than a dynamical time ago, t_infall < t_dyn. Combined with estimated dynamical times t_dyn ~ 3-5 Gyr and SED fitting results for the time at which satellites stopped forming stars, t_quench ~ 6 Gyr, we infer that for a significant fraction of the satellites, star formation quenched before those satellites entered their current hosts. The result holds for red satellites over a large range of cluster-centric distances 0.1 - 0.6 Mpc/h. We discuss the implications of this result for models of galaxy formation.

Intrinsic alignments in redMaPPer clusters – I. Central galaxy alignments and angular segregation of satellites

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94817 members within 0.1<z<0.35, based on the redMaPPer cluster catalog constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centering probability, and redder color. Satellites with redder color, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation toward their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.

Constraining the mass–richness relationship of redMaPPer clusters with angular clustering

The potential of using cluster clustering for calibrating the mass-observable relation of galaxy clusters has been recognized theoretically for over a decade. Here, we demonstrate the feasibility of this technique to achieve high precision mass calibration using redMaPPer clusters in the Sloan Digital Sky Survey North Galactic Cap. By including cross-correlations between several richness bins in our analysis we significantly improve the statistical precision of our mass constraints. The amplitude of the mass-richness relation is constrained to 7% statistical precision. However, the error budget is systematics dominated, reaching an 18% total error that is dominated by theoretical uncertainty in the bias-mass relation for dark matter halos. We perform a detailed treatment of the effects of assembly bias on our analysis, finding that the contribution of such effects to our parameter uncertainties is somewhat greater than that of measurement noise. We confirm the results from Miyatake et al. (2015) that the clustering amplitude of redMaPPer clusters depends on galaxy concentration, and provide additional evidence in support of this effect being due to some form of assembly bias. The results presented here demonstrate the power of cluster clustering for mass calibration and cosmology provided the current theoretical systematics can be ameliorated.

Observing dynamical friction in galaxy clusters

We present a novel method to detect the effects of dynamical friction in observed galaxy clusters. Following accretion into clusters, massive satellite galaxies will backsplash to systematically smaller radii than less massive satellites, an effect that may be detected by stacking the number density profiles of galaxies around clusters. We show that this effect may be understood using a simple toy model which reproduces the trends with halo properties observed in simulations. We search for this effect using SDSS redMaPPer clusters with richness 010 < λ < 2, and find that bright (Mi < −21.5) satellites have smaller splashback radii than fainter (0Mi > −2) satellites at 99% confidence.

Galaxy cluster mass estimation from stacked spectroscopic analysis

We use simulated galaxy surveys to study: i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and ii) the accuracy of a mean dynamical cluster mass, $M_\sigma(\lambda)$, derived from stacked pairwise spectroscopy of clusters with richness $\lambda$. Using $\sim\! 130,000$ galaxy pairs patterned after the SDSS redMaPPer cluster sample study of Rozo et al. (2015 RMIV), we show that the pairwise velocity PDF of central--satellite pairs with $m_i < 19$ in the simulation matches the form seen in RMIV. Through joint membership matching, we deconstruct the main Gaussian velocity component into its halo contributions, finding that the top-ranked halo contributes $\sim 60\%$ of the stacked signal. The halo mass scale inferred by applying the virial scaling of Evrard et al. (2008) to the velocity normalization matches, to within a few percent, the log-mean halo mass derived through galaxy membership matching. We apply this approach, along with mis-centering and galaxy velocity bias corrections, to estimate the log-mean matched halo mass at $z=0.2$ of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al. (2015), we find $\langle \ln(M_{200c})|\lambda \rangle = \ln(M_{30}) + \alpha_m \ln(\lambda/30)$ with $M_{30} = 1.56 \pm 0.35 \times 10^{14} M_\odot$ and $\alpha_m = 1.31 \pm 0.06_{stat} \pm 0.13_{sys}$. Systematic uncertainty in the velocity bias of satellite galaxies overwhelmingly dominates the error budget.

Measuring subhalo mass in redMaPPer clusters with CFHT Stripe 82 Survey

We use the shear catalog from the CFHT Stripe-82 Survey to measure the subhalo masses of satellite galaxies in redMaPPer clusters. Assuming a Chabrier Initial Mass Function (IMF) and a truncated NFW model for the subhalo mass distribution, we find that the sub-halo mass to galaxy stellar mass ratio increases as a function of projected halo-centric radius $r_p$, from $M_{\rm sub}/M_{\rm star}=4.43^{+ 6.63}_{- 2.23}$ at $r_p \in [0.1,0.3]$ $h^{-1}Mpc$ to $M_{\rm sub}/M_{\rm star}=75.40^{+ 19.73}_{- 19.09}$ at $r_p \in [0.6,0.9]$ $h^{-1}Mpc$. We also investigate the dependence of subhalo masses on stellar mass by splitting satellite galaxies into two stellar mass bins: $10<\log(M_{\rm star}/M_{\rm sun})<10.5$ and $11<\log(M_{\rm star}/M_{\rm sun})<12$. The best-fit subhalo mass of the more massive satellite galaxy bin is larger than that of the less massive satellites: $\log(M_{\rm sub}/M_{\rm sun})=11.14 ^{+ 0.66 }_{- 0.73}$ ($M_{\rm sub}/M_{\rm star}=19.5^{+19.8}_{-17.9}$) versus $\log(M_{\rm sub}/M_{\rm sun})=12.38 ^{+ 0.16 }_{- 0.16}$ ($M_{\rm sub}/M_{\rm star}=21.1^{+7.4}_{-7.7}$).

MASS–CONCENTRATION RELATION OF CLUSTERS OF GALAXIES FROM CFHTLenS

Based on weak lensing data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), in this paper we study the mass-concentration ($M$-$c$) relation for $\sim 200$ redMaPPer clusters in the fields. We extract the $M$-$c$ relation by measuring the density profiles of individual clusters instead of using stacked weak lensing signals. By performing Monte Carlo simulations, we demonstrate that although the signal-to-noise ratio for each individual cluster is low, the unbiased $M$-$c$ relation can still be reliably derived from a large sample of clusters by carefully taking into account the impacts of shape noise, cluster center offset, dilution effect from member or foreground galaxies, and the projection effect. Our results show that within error bars the derived $M$-$c$ relation for redMaPPer clusters is in agreement with simulation predictions. There is a weak deviation in that the halo concentrations calibrated by Monte Carlo simulations are somewhat higher than that predicted from ${\it Planck}$ cosmology.

Cosmic web reconstruction through density ridges: method and algorithm

The detection and characterization of filamentary structures in the cosmic web allows cosmologists to constrain parameters that dictates the evolution of the Universe. While many filament estimators have been proposed, they generally lack estimates of uncertainty, reducing their inferential power. In this paper, we demonstrate how one may apply the Subspace Constrained Mean Shift (SCMS) algorithm (Ozertem and Erdogmus (2011); Genovese et al. (2012)) to uncover filamentary structure in galaxy data. The SCMS algorithm is a gradient ascent method that models filaments as density ridges, one-dimensional smooth curves that trace high-density regions within the point cloud. We also demonstrate how augmenting the SCMS algorithm with bootstrap-based methods of uncertainty estimation allows one to place uncertainty bands around putative filaments. We apply the SCMS method to datasets sampled from the P3M N-body simulation, with galaxy number densities consistent with SDSS and WFIRST-AFTA and to LOWZ and CMASS data from the Baryon Oscillation Spectroscopic Survey (BOSS). To further assess the efficacy of SCMS, we compare the relative locations of BOSS filaments with galaxy clusters in the redMaPPer catalog, and find that redMaPPer clusters are significantly closer (with p-values $< 10^{-9}$) to SCMS-detected filaments than to randomly selected galaxies.

RedMaPPer – IV. Photometric membership identification of red cluster galaxies with 1 per cent precision

In order to study the galaxy population of galaxy clusters with photometric data one must be able to accurately discriminate between cluster members and non-members. The redMaPPer cluster finding algorithm treats this problem probabilistically. Here, we utilize SDSS and GAMA spectroscopic membership rates to validate the redMaPPer membership probability estimates for clusters with $z\in[0.1,0.3]$. We find small - but correctable - biases, sourced by three different systematics. The first two were expected a priori, namely blue cluster galaxies and correlated structure along the line of sight. The third systematic is new: the redMaPPer template fitting exhibits a non-trivial dependence on photometric noise, which biases the original redMaPPer probabilities when utilizing noisy data. After correcting for these effects, we find exquisite agreement ($\approx 1\%$) between the photometric probability estimates and the spectroscopic membership rates, demonstrating that we can robustly recover cluster membership estimates from photometric data alone. As a byproduct of our analysis we find that on average unavoidable projection effects from correlated structure contribute $\approx 6\%$ of the richness of a redMaPPer galaxy cluster. This work also marks the second public release of the SDSS redMaPPer cluster catalog.

Luminous red galaxies in clusters: central occupation, spatial distributions and miscentring

Luminous Red Galaxies (LRG) from the Sloan Digital Sky Survey are considered among the best understood samples of galaxies, and they are employed in a broad range of cosmological studies. Because they form a relatively homogeneous population, with high stellar masses and red colors, they are expected to occupy halos in a relatively simple way. In this paper, we study how LRGs occupy massive halos via direct counts in clusters and we reveal several unexpected trends suggesting that the connection between LRGs and dark matter halos may not be straightforward. Using the redMaPPer cluster catalog, we derive the central occupation of LRGs as a function richness, Ncen({\lambda}). Assuming no correlation between cluster mass and central galaxy luminosity at fixed richness, we show that clusters contain a significantly lower fraction of central LRGs than predicted from the two-point correlation function. At halo masses of 10^14.5 Msun, we find Ncen=0.73, compared to Ncen of 0.89 from correlation studies. Our central occupation function for LRGs converges to 0.95 at large halo masses. A strong anti-correlation between central luminosity and cluster mass at fixed richness is required to reconcile our results with those based on clustering studies. We also derive P_BNC, the probability that the brightest cluster member is not the central galaxy. We find P_BNC ~ 20-30% which is a factor of ~2 lower than the value found by Skibba et al. 2011. Finally, we study the radial offsets of bright non-central LRGs from cluster centers and show that bright non-central LRGs follow a different radial distribution compared to red cluster members, which follow a Navarro-Frank-White profile. This work demonstrates that even the most massive clusters do not always have an LRG at the center, and that the brightest galaxy in a cluster is not always the central galaxy.

RedMaPPer – III. A detailed comparison of the Planck 2013 and SDSS DR8 redMaPPer cluster catalogues

We compare the Planck Sunyaev-Zeldovich (SZ) cluster sample (PSZ1) to the Sloan Digital Sky Survey (SDSS) redMaPPer catalog, finding that all Planck clusters within the redMaPPer mask and within the redshift range probed by redMaPPer are contained in the redMaPPer cluster catalog. These common clusters define a tight scaling relation in the richness-SZ mass ($\lambda$--$M_{SZ}$) plane, with an intrinsic scatter in richness of $\sigma_{\lambda|M_{SZ}} = 0.266 \pm 0.017$. The corresponding intrinsic scatter in true cluster halo mass at fixed richness is $\approx 21\%$. The regularity of this scaling relation is used to identify failures in both the redMaPPer and Planck cluster catalogs. Of the 245 galaxy clusters in common, we identify three failures in redMaPPer and 36 failures in the PSZ1. Of these, at least 12 are due to clusters whose optical counterpart was correctly identified in the PSZ1, but where the quoted redshift for the optical counterpart in the external data base used in the PSZ1 was incorrect. The failure rates for redMaPPer and the PSZ1 are $1.2\%$ and $14.7\%$ respectively, or 9.8% in the PSZ1 after subtracting the external data base errors. We have further identified 5 PSZ1 sources that suffer from projection effects (multiple rich systems along the line-of-sight of the SZ detection) and 17 new high redshift ($z\gtrsim 0.6$) cluster candidates of varying degrees of confidence. Should all of the high-redshift cluster candidates identified here be confirmed, we will have tripled the number of high redshift Planck clusters in the SDSS region. Our results highlight the power of multi-wavelength observations to identify and characterize systematic errors in galaxy cluster data sets, and clearly establish photometric data both as a robust cluster finding method, and as an important part of defining clean galaxy cluster samples.

Comparing gravitational redshifts of SDSS galaxy clusters with the magnified redshift enhancement of background BOSS galaxies

A clean measurement of the evolution of the galaxy cluster mass function can significantly improve our understanding of cosmology from the rapid growth of cluster masses below z < 0.5. Here we examine the consistency of cluster catalogues selected from the SDSS by applying two independent gravity-based methods using all available spectroscopic redshifts from the DR10 release. First, we detect a gravitational redshift related signal for 20,119 and 13,128 clusters with spectroscopic redshifts contained in the GMBCG and redMaPPer catalogues, respectively, at a level of $\sim - 10$ km s$^{-1}$. This we show is consistent with the magnitude expected using the richness-mass relations provided by the literature and after applying recently clarified relativistic and flux bias corrections. This signal is also consistent with the richest clusters in the larger catalogue of Wen et al. (2012), corresponding to $M_{200m} \gtrsim 2 \times 10^{14}\,\mathrm{M}_\odot\,h^{-1}$, however we find no significant detection of gravitational redshift signal for less riched clusters, which may be related to bulk motions from substructure and spurious cluster detections. Second, we find all three catalogues generate mass-dependent levels of lensing magnification bias, which enhances the mean redshift of flux-selected background galaxies from the BOSS survey. The magnitude of this lensing effect is generally consistent with the corresponding richness-mass relations advocated for the surveys. We conclude that all catalogues comprise a high proportion of reliable clusters, and that the GMBCG and redMaPPer cluster finder algorithms favor more relaxed clusters with a meaningful gravitational redshift signal, as anticipated by the red-sequence colour selection of the GMBCG and redMaPPer samples.

The X-CLASS−redMaPPer galaxy cluster comparison

We performed a detailed and, for a large part interactive, analysis of the matching output between the X-CLASS and redMaPPer cluster catalogues. 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 a 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. Main results show that neither of the wavebands misses any massive cluster (as coded by X-ray luminosity or optical richness). After correcting for obvious pipeline short-comings (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 centers. The fraction of clusters totally dominated by AGN-type emission appears to be of the order of 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 fact that the X-CLASS sample extends further out than redMaPPer (z<1 vs z<0.6); extending the correlation down to a richness of 5, raises the matching rate to ~ 65%.

RedMaPPer II: X-RAY AND SZ PERFORMANCE BENCHMARKS FOR THE SDSS CATALOG

We evaluate the performance of the SDSS DR8 redMaPPer photometric cluster catalog by comparing it to overlapping X-ray and SZ selected catalogs from the literature. We confirm the redMaPPer photometric redshifts are nearly unbiased (<\Delta z> < 0.005), have low scatter (\sigma_z ~ 0.006-0.02, depending on redshift), and have a low catastrophic failure rate (~ 1%). Both the T_X-\lambda\ and Mgas-\lambda\ scaling relations are consistent with a mass scatter of \sigma_{\ln M|\lambda} ~ 25%, albeit with a ~ 1% outlier rate due to projection effects. This failure rate is somewhat lower than that expected for the full cluster sample, but is consistent with the additional selection effects introduced by our reliance on X-ray and SZ selected reference cluster samples. Where the redMaPPer DR8 catalog is volume limited (z < 0.35), the catalog is 100% complete above T_X > 3.5 keV, and L_X > 2\times 10^{44} erg/s, decreasing to 90% completeness at L_X ~ 10^{43} erg/s. All rich (\lambda > 100), low redshift (z < 0.25) redMaPPer clusters are X-ray detected in the ROSAT All Sky Survey (RASS), and 86% of the clusters are correctly centered. Compared to other SDSS photometric cluster catalogs, redMaPPer has the highest completeness and purity, and the best photometric redshift performance, though some algorithms do achieve comparable performance to redMaPPer in subsets of the above categories and/or in limited redshift ranges. The redMaPPer richness is clearly the one that best correlates with X-ray temperature and gas mass. Most algorithms (including redMaPPer) have very similar centering performance, with only one exception which performs worse.