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Title: Probabilistic Cosmological Mass Mapping from Weak Lensing Shear

Abstract

© 2017. The American Astronomical Society. All rights reserved.. 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.

Authors:
ORCiD logo; ; ; ; ORCiD logo;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1476480
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
The Astrophysical Journal (Online)
Additional Journal Information:
Journal Volume: 839; Journal Issue: 1; Journal ID: ISSN 1538-4357
Publisher:
Institute of Physics (IOP)
Country of Publication:
United States
Language:
English

Citation Formats

Schneider, M. D., Ng, K. Y., Dawson, W. A., Marshall, P. J., Meyers, J. E., and Bard, D. J. Probabilistic Cosmological Mass Mapping from Weak Lensing Shear. United States: N. p., 2017. Web. doi:10.3847/1538-4357/839/1/25.
Schneider, M. D., Ng, K. Y., Dawson, W. A., Marshall, P. J., Meyers, J. E., & Bard, D. J. Probabilistic Cosmological Mass Mapping from Weak Lensing Shear. United States. doi:10.3847/1538-4357/839/1/25.
Schneider, M. D., Ng, K. Y., Dawson, W. A., Marshall, P. J., Meyers, J. E., and Bard, D. J. Mon . "Probabilistic Cosmological Mass Mapping from Weak Lensing Shear". United States. doi:10.3847/1538-4357/839/1/25. https://www.osti.gov/servlets/purl/1476480.
@article{osti_1476480,
title = {Probabilistic Cosmological Mass Mapping from Weak Lensing Shear},
author = {Schneider, M. D. and Ng, K. Y. and Dawson, W. A. and Marshall, P. J. and Meyers, J. E. and Bard, D. J.},
abstractNote = {© 2017. The American Astronomical Society. All rights reserved.. 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.},
doi = {10.3847/1538-4357/839/1/25},
journal = {The Astrophysical Journal (Online)},
issn = {1538-4357},
number = 1,
volume = 839,
place = {United States},
year = {2017},
month = {4}
}

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