On the Level of Cluster Assembly Bias in SDSS

Ying Zu; Rachel Mandelbaum; Melanie Simet; Eduardo Rozo; Eli S. Rykoff

doi:10.1093/mnras/stx1264

paper

On the Level of Cluster Assembly Bias in SDSS

arXiv:1611.00366 · doi:10.1093/mnras/stx1264

Abstract

Recently, several studies have discovered a strong discrepancy between the large-scale clustering biases of two subsamples of galaxy clusters at the same halo mass, split by their average projected membership distances $R_{mem}$ . The level of this discrepancy significantly exceeds the maximum halo assembly bias signal predicted by LCDM. In this study, we explore whether some of the clustering bias differences could be caused by biases in $R_{mem}$ due to projection effects from other systems along the line-of-sight. We thoroughly investigate the halo assembly bias of the photometrically-detected redMaPPer clusters in SDSS, by defining a new variant of the average membership distance estimator $R ~_{mem}$ that is more robust against projection effects in the cluster membership identification. Using the angular mark correlation functions of clusters, we show that the large-scale bias differences when splitting by $R_{mem}$ can be largely attributed to such projection effects. After splitting by $R ~_{mem}$ , the anomalously large signal is reduced, giving a ratio of $1.02 \pm 0.14$ between the two clustering biases as measured from weak lensing. Using a realistic mock cluster catalog, we predict that the bias ratio between two $R ~_{mem}$ -split subsamples should be $< 1.10$ , which is at least 60% weaker than the maximum halo assembly bias signal (1.24) when split by halo concentration. Therefore, our results demonstrate that the level of halo assembly bias exhibited by redMaPPer clusters in SDSS is consistent with the LCDM prediction. With a ten-fold increase in cluster numbers, deeper ongoing surveys will enable a more robust detection of halo assembly bias. Our findings also have important implications for how projection effects and their impact on cluster cosmology can be quantified in photometric cluster catalogs.

11 pages, 8 figures, MNRAS published

On the Level of Cluster Assembly Bias in SDSS

Abstract

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