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Three-Dimensional Reconstruction of Weak-Lensing Mass Maps with a Sparsity Prior. II. Weighing Triaxial Cluster Halos
Shouzhuo Yang, Xiangchong Li, Naoki Yoshida
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Continuing work presented in Li et al. (2021), we performed a series of tests to our high-resolution three-dimensional mass map reconstruction algorithm \splinv{}. We test the mass reconstruction accuracy against realistic mock catalogs generated using shear field produced by triaxial halos with the inner density profile of ρ∝r⁻¹ and of ρ∝r^(-1.5). The galaxy shape noise is modeled based on the Year-1 Subaru Hyper Suprime-Cam (HSC) Survey. After reviewing mathematical details of our algorithm and dark matter halo models, we determine an optimal value of the coefficient of the adaptive LASSO regression penalty term for single halo reconstruction. We successfully measure halo masses for massive triaxial halos; the mass determination accuracy is 5 percent for halos with M = 10^(14.6) M_⊙ at 0.0625≤z ≤0.2425, and 5 percent for those with 10^(14.8) M_⊙ at 0.0625≤z ≤0.4675, and 20 percent for M= 10^(15.0) M_⊙ and M=10^(15.2) M_⊙ in the redshift range 0.0625≤z ≤0.4675. The redshift estimate accuracy is consistently below Δz /z ≤0.05 for the above halo masses in the range 0.1525≤z ≤0.4675. We also demonstrate that the orientation of triaxial halos and systematic error in our halo model do not affect reconstruction result significantly. Finally, we present results from reconstruction of mass distribution using shear catalogs produced by multiple halos, to show \splinv{}'s capability using realistic shear maps from ongoing and future galaxy surveys.
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