The weak gravitational lensing of galaxy clusters is a valuable tool. The deflection of light around a lens is solely dependent on the underlying distribution of foreground mass, and independent of tracers of mass such as the mass to light ratio and kinematics. As a direct probe of mass, weak lensing serves as an independent calibration of mass-observable relationships. These massive clusters are objects of great interest to astronomers, as their abundance is dependent on the conditions of the early universe, and accurate counts of clusters serve as a test of cosmological model. Upcoming surveys, such as LSST and DES, promise to push the limit of observable weak lensing, detecting clusters and sources at higher redshift than has ever been detected before. This makes accurate counts of clusters of a given mass and redshift, and proper calibration of mass-observable relationships, vital to cosmological studies. We used M> 1013.5 h-1M ☉ halos from the MultiDark Planck simulation at z 0.5 to study the behavior of the reduced shear in clusters. We generated 2D maps of convergence and shear the halos using the GLAMER lensing library. Using these maps, we simulated observations of randomly placed background sources, and generate azimuthal averages of the shear. This reduced shear profile, and the true reduced shear profile of the halo, is fit using analytical solutions for shear of the NFW, Einasto, and truncated NFW density profile. The masses of these density profiles are then compared to the total halo masses from the halo catalogs. We find that fits to the reduced shear for halos extending past ≈ 2 h-1Mpc are fits to the noise of large scale structure along the line of sight. This noise is largely in the 45° rotated component to the reduced tangential shear, and is a breakdown in the approximation of gtan ≈ gnot required for density profile fitting of clusters. If fits are constrained to a projected radii of < 2 h-1Mpc, we see massively improved fits insensitive to the amount of structure present along the line of sight.
- Pub Date:
- February 2017