Cosmological constraints from current and upcoming galaxy cluster surveys are limited by the accuracy of cluster mass calibration. In particular, optically identified galaxy clusters are prone to selection effects that can bias the weak lensing mass calibration. We investigate the selection bias of the stacked cluster lensing signal associated with optically selected clusters, using clusters identified by the redMaPPer algorithm in the Buzzard simulations as a case study. We find that at a given cluster halo mass, the residuals of redMaPPer richness and weak lensing signal are positively correlated. As a result, for a given richness selection, the stacked lensing signal is biased high compared with what we would expect from the underlying halo mass probability distribution. The cluster lensing selection bias can thus lead to overestimated mean cluster mass and biased cosmology results. We show that the lensing selection bias exhibits a strong scale-dependence and is approximately 20 to 60 percent for ΔΣ at large scales. This selection bias largely originates from spurious member galaxies within +/- 20 to 60 Mpc/h along the line of sight, highlighting the importance of quantifying projection effects associated with the broad redshift distribution of member galaxies in photometric cluster surveys. While our results qualitatively agree with those in the literature, accurate quantitative modelling of the selection bias is needed to achieve the goals of cluster lensing cosmology and will require synthetic catalogues covering a wide range of galaxy-halo connection models.
@article{arxiv.2203.05416,
title = {Optical selection bias and projection effects in stacked galaxy cluster weak lensing},
author = {Hao-Yi Wu and Matteo Costanzi and Chun-Hao To and Andrés N. Salcedo and David H. Weinberg and James Annis and Sebastian Bocquet and Maria Elidaiana da Silva Pereira and Joseph DeRose and Johnny Esteves and Arya Farahi and Sebastian Grandis and Eduardo Rozo and Eli S. Rykoff and Tamás N. Varga and Risa H. Wechsler and Chenxiao Zeng and Yuanyuan Zhang and Zhuowen Zhang},
journal= {arXiv preprint arXiv:2203.05416},
year = {2022}
}
Comments
16 pages, 16 figures; replaced to match published version