Predicting weak lensing statistics from halo mass reconstructions - Final Paper
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
As dark matter does not absorb or emit light, its distribution in the universe must be inferred through indirect effects such as the gravitational lensing of distant galaxies. While most sources are only weakly lensed, the systematic alignment of background galaxies around a foreground lens can constrain the mass of the lens which is largely in the form of dark matter. In this paper, I have implemented a framework to reconstruct all of the mass along lines of sight using a best-case dark matter halo model in which the halo mass is known. This framework is then used to make predictions of the weak lensing of 3,240 generated source galaxies through a 324 arcmin² field of the Millennium Simulation. The lensed source ellipticities are characterized by the ellipticity-ellipticity and galaxy-mass correlation functions and compared to the same statistic for the intrinsic and ray-traced ellipticities. In the ellipticity-ellipticity correlation function, I and that the framework systematically under predicts the shear power by an average factor of 2.2 and fails to capture correlation from dark matter structure at scales larger than 1 arcminute. The model predicted galaxy-mass correlation function is in agreement with the ray-traced statistic from scales 0.2 to 0.7 arcminutes, but systematically underpredicts shear power at scales larger than 0.7 arcminutes by an average factor of 1.2. Optimization of the framework code has reduced the mean CPU time per lensing prediction by 70% to 24 ± 5 ms. Physical and computational shortcomings of the framework are discussed, as well as potential improvements for upcoming work.
- Research Organization:
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- AC02-76SF00515
- OSTI ID:
- 1213198
- Report Number(s):
- SLAC-TN-15-027
- Resource Relation:
- Conference: Boston, MA (United States), 19-23 Jul 2015
- Country of Publication:
- United States
- Language:
- English
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