Probabilistic Cosmological Mass Mapping from Weak Lensing Shear
- Lawrence Livermore National Laboratory, Livermore, CA 94551 (United States)
- University of California, Davis, Davis, CA 95616 (United States)
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, CA 94035 (United States)
- Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)
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.
- OSTI ID:
- 22661160
- Journal Information:
- Astrophysical Journal, Journal Name: Astrophysical Journal Journal Issue: 1 Vol. 839; ISSN ASJOAB; ISSN 0004-637X
- Country of Publication:
- United States
- Language:
- English
The correspondence between convergence peaks from weak lensing and massive dark matter haloes
|
journal | May 2018 |
| Merging Cluster Collaboration: A Panchromatic Atlas of Radio Relic Mergers | text | January 2018 |
Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: application to DES SV
|
journal | May 2018 |
Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: Application to DES SV
|
text | January 2018 |
Merging Cluster Collaboration: A Panchromatic Atlas of Radio Relic Mergers
|
journal | September 2019 |
Similar Records
HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR