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Full-Text Articles in Physics
Self-Calibrating Optical Galaxy Cluster Selection Bias Using Cluster, Galaxy, And Shear Cross-Correlations, Chenxiao Zeng, Andrés N. Salcedo, Hao-Yi Wu, Christopher M. Hirata
Self-Calibrating Optical Galaxy Cluster Selection Bias Using Cluster, Galaxy, And Shear Cross-Correlations, Chenxiao Zeng, Andrés N. Salcedo, Hao-Yi Wu, Christopher M. Hirata
Physics Faculty Publications and Presentations
The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition …
Modelling Galaxy Cluster Triaxiality In Stacked Cluster Weak Lensing Analyses, Hao-Yi Wu
Modelling Galaxy Cluster Triaxiality In Stacked Cluster Weak Lensing Analyses, Hao-Yi Wu
Physics Faculty Publications and Presentations
Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude …
Optical Selection Bias And Projection Effects In Stacked Galaxy Cluster Weak Lensing, Hao-Yi Wu
Optical Selection Bias And Projection Effects In Stacked Galaxy Cluster Weak Lensing, Hao-Yi Wu
Physics Faculty Publications and Presentations
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 …
Clmm: A Lsst-Desc Cluster Weak Lensing Mass Modeling Library For Cosmology, H. Wu
Clmm: A Lsst-Desc Cluster Weak Lensing Mass Modeling Library For Cosmology, H. Wu
Physics Faculty Publications and Presentations
We present the v1.0 release of CLMM, an open source PYTHON library for the estimation of the weak lensing masses of clusters of galaxies. CLMM is designed as a stand-alone toolkit of building blocks to enable end-to-end analysis pipeline validation for upcoming cluster cosmology analyses such as the ones that will be performed by the Vera C. Rubin Legacy Survey of Space and Time-Dark Energy Science Collaboration (LSST-DESC). Its purpose is to serve as a flexible, easy-to-install, and easy-to-use interface for both weak lensing simulators and observers and can be applied to real and mock data to study the systematics …