508 research outputs found

    Robust Optical Richness Estimation with Reduced Scatter

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    Reducing the scatter between cluster mass and optical richness is a key goal for cluster cosmology from photometric catalogs. We consider various modifications to the red-sequence matched filter richness estimator of Rozo et al. (2009), and evaluate their impact on the scatter in X-ray luminosity at fixed richness. Most significantly, we find that deeper luminosity cuts can reduce the recovered scatter, finding that sigma_lnLX|lambda=0.63+/-0.02 for clusters with M_500c >~ 1.6e14 h_70^-1 M_sun. The corresponding scatter in mass at fixed richness is sigma_lnM|lambda ~ 0.2-0.3 depending on the richness, comparable to that for total X-ray luminosity. We find that including blue galaxies in the richness estimate increases the scatter, as does weighting galaxies by their optical luminosity. We further demonstrate that our richness estimator is very robust. Specifically, the filter employed when estimating richness can be calibrated directly from the data, without requiring a-priori calibrations of the red-sequence. We also demonstrate that the recovered richness is robust to up to 50% uncertainties in the galaxy background, as well as to the choice of photometric filter employed, so long as the filters span the 4000 A break of red-sequence galaxies. Consequently, our richness estimator can be used to compare richness estimates of different clusters, even if they do not share the same photometric data. Appendix 1 includes "easy-bake" instructions for implementing our optimal richness estimator, and we are releasing an implementation of the code that works with SDSS data, as well as an augmented maxBCG catalog with the lambda richness measured for each cluster.Comment: Submitted to ApJ. 20 pages in emulateapj forma

    Galaxy Cluster Mass Estimation from Stacked Spectroscopic Analysis

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    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, Mσ(λ)M_\sigma(\lambda), derived from stacked pairwise spectroscopy of clusters with richness λ\lambda. Using  ⁣130,000\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 mi<19m_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 60%\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=0.2z=0.2 of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al. (2015), we find ln(M200c)λ=ln(M30)+αmln(λ/30)\langle \ln(M_{200c})|\lambda \rangle = \ln(M_{30}) + \alpha_m \ln(\lambda/30) with M30=1.56±0.35×1014MM_{30} = 1.56 \pm 0.35 \times 10^{14} M_\odot and αm=1.31±0.06stat±0.13sys\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.Comment: 14 pages, 7 figure

    Intrinsic Alignment in redMaPPer clusters -- II. Radial alignment of satellites toward cluster centers

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    We study the orientations of satellite galaxies in redMaPPer clusters constructed from the Sloan Digital Sky Survey at 0.1<z<0.350.1<z<0.35 to determine whether there is any preferential tendency for satellites to point radially toward cluster centers. We analyze the satellite alignment (SA) signal based on three shape measurement methods (re-Gaussianization, de Vaucouleurs, and isophotal shapes), which trace galaxy light profiles at different radii. The measured SA signal depends on these shape measurement methods. We detect the strongest SA signal in isophotal shapes, followed by de Vaucouleurs shapes. While no net SA signal is detected using re-Gaussianization shapes across the entire sample, the observed SA signal reaches a statistically significant level when limiting to a subsample of higher luminosity satellites. We further investigate the impact of noise, systematics, and real physical isophotal twisting effects in the comparison between the SA signal detected via different shape measurement methods. Unlike previous studies, which only consider the dependence of SA on a few parameters, here we explore a total of 17 galaxy and cluster properties, using a statistical model averaging technique to naturally account for parameter correlations and identify significant SA predictors. We find that the measured SA signal is strongest for satellites with the following characteristics: higher luminosity, smaller distance to the cluster center, rounder in shape, higher bulge fraction, and distributed preferentially along the major axis directions of their centrals. Finally, we provide physical explanations for the identified dependences, and discuss the connection to theories of SA.Comment: 25 pages, 16 figures, 7 tables, accepted to MNRAS. Main statistical analysis tool changed, with the results remain simila

    Cosmological Constraints from the SDSS maxBCG Cluster Catalog

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    We use the abundance and weak lensing mass measurements of the SDSS maxBCG cluster catalog to simultaneously constrain cosmology and the richness--mass relation of the clusters. Assuming a flat \LambdaCDM cosmology, we find \sigma_8(\Omega_m/0.25)^{0.41} = 0.832\pm 0.033 after marginalization over all systematics. In common with previous studies, our error budget is dominated by systematic uncertainties, the primary two being the absolute mass scale of the weak lensing masses of the maxBCG clusters, and uncertainty in the scatter of the richness--mass relation. Our constraints are fully consistent with the WMAP five-year data, and in a joint analysis we find \sigma_8=0.807\pm 0.020 and \Omega_m=0.265\pm 0.016, an improvement of nearly a factor of two relative to WMAP5 alone. Our results are also in excellent agreement with and comparable in precision to the latest cosmological constraints from X-ray cluster abundances. The remarkable consistency among these results demonstrates that cluster abundance constraints are not only tight but also robust, and highlight the power of optically-selected cluster samples to produce precision constraints on cosmological parameters.Comment: comments welcom

    The Mean and Scatter of the Velocity Dispersion-Optical Richness Relation for maxBCG Galaxy Clusters

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    The distribution of galaxies in position and velocity around the centers of galaxy clusters encodes important information about cluster mass and structure. Using the maxBCG galaxy cluster catalog identified from imaging data obtained in the Sloan Digital Sky Survey, we study the BCG-galaxy velocity correlation function. By modeling its non-Gaussianity, we measure the mean and scatter in velocity dispersion at fixed richness. The mean velocity dispersion increases from 202+/-10 km/s for small groups to more than 854+/-102 km/s for large clusters. We show the scatter to be at most 40.5+/-3.5%, declining to 14.9+/-9.4% in the richest bins. We test our methods in the C4 cluster catalog, a spectroscopic cluster catalog produced from the Sloan Digital Sky Survey DR2 spectroscopic sample, and in mock galaxy catalogs constructed from N-body simulations. Our methods are robust, measuring the scatter to well within one-sigma of the true value, and the mean to within 10%, in the mock catalogs. By convolving the scatter in velocity dispersion at fixed richness with the observed richness space density function, we measure the velocity dispersion function of the maxBCG galaxy clusters. Although velocity dispersion and richness do not form a true mass-observable relation, the relationship between velocity dispersion and mass is theoretically well characterized and has low scatter. Thus our results provide a key link between theory and observations up to the velocity bias between dark matter and galaxies.Comment: 25 pages, 15 figures, 2 tables, published in Ap
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