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Probabilistic cosmological mass mapping from weak lensing shear

Journal Article · · The Astrophysical Journal (Online)
 [1];  [2];  [1];  [3];  [4];  [5]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Univ. of California, Davis, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
  4. Princeton Univ., Princeton, NJ (United States)
  5. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
+ Show Author Affiliations

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.

Research Organization:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE Laboratory Directed Research and Development (LDRD) Program
Contributing Organization:
Univ. of California, Davis, CA (United States); Stanford Univ., Stanford, CA (United States)
Grant/Contract Number:
AC52-07NA27344; AC02-05CH11231
OSTI ID:
1357351
Report Number(s):
LLNL-JRNL--697380
Journal Information:
The Astrophysical Journal (Online), Journal Name: The Astrophysical Journal (Online) Journal Issue: 1 Vol. 839; ISSN 1538-4357
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English

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Cited By (5)

Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: application to DES SV journal May 2018
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 journal September 2019
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 text January 2018

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Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
catalogs
cosmology: observations
gravitational lensing: weak
methods: data analysis
methods: statistical
surveys