Probabilistic cosmological mass mapping from weak lensing shear [electronic resource].
- Washington, D.C. : United States. Dept. of Energy. Office of Advanced Scientific Computing Research, 2017. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- Article numbers 25 : digital, PDF file
- Additional Creators:
- Lawrence Livermore National Laboratory, United States. Department of Energy. Office of Advanced Scientific Computing Research, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Here, we infer gravitational lensing shear and convergence fields from galaxy ellipticity catalogs under a spatial process prior for the lensing potential. We demonstrate the performance of our algorithm with simulated Gaussian-distributed cosmological lensing shear maps and a reconstruction of the mass distribution of the merging galaxy cluster Abell 781 using galaxy ellipticities measured with the Deep Lens Survey. Given interim posterior samples of lensing shear or convergence fields on the sky, we describe an algorithm to infer cosmological parameters via lens field marginalization. In the most general formulation of our algorithm we make no assumptions about weak shear or Gaussian-distributed shape noise or shears. Because we require solutions and matrix determinants of a linear system of dimension that scales with the number of galaxies, we expect our algorithm to require parallel high-performance computing resources for application to ongoing wide field lensing surveys.
- Published through SciTech Connect., 04/10/2017., "llnl-jrnl--697380", The Astrophysical Journal (Online) 839 1 ISSN 1538-4357 AM, and M. D. Schneider; K. Y. Ng; W. A. Dawson; P. J. Marshall; J. E. Meyers; D. J. Bard.
- Funding Information:
- AC52-07NA27344 and AC02-05CH11231
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