U.S. Department of EnergyOffice of Scientific and Technical Information
Atomic Inference from Weak Gravitational Lensing Data
Abstract
We present a novel approach to reconstructing the projected mass distribution from the sparse and noisy weak gravitational lensing shear data. The reconstructions are regularized via the knowledge gained from numerical simulations of clusters, with trial mass distributions constructed from n NFW profile ellipsoidal components. The parameters of these ''atoms'' are distributed a priori as in the simulated clusters. Sampling the mass distributions from the atom parameter probability density function allows estimates of the properties of the mass distribution to be generated, with error bars. The appropriate number of atoms is inferred from the data itself via the Bayesian evidence, and is typically found to be small, reecting the quality of the data. Ensemble average mass maps are found to be robust to the details of the noise realization, and succeed in recovering the demonstration input mass distribution (from a realistic simulated cluster) over a wide range of scales. As an application of such a reliable mapping algorithm, we comment on the residuals of the reconstruction and the implications for predicting convergence and shear at specific points on the sky.
- Authors:
- Publication Date:
- Research Org.:
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 877491
- Report Number(s):
- SLAC-PUB-11563
Journal ID: ISSN 0035-8711; MNRAA4; astro-ph/0511287; TRN: US200608%%57
- DOE Contract Number:
- AC02-76SF00515
- Resource Type:
- Journal Article
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Additional Journal Information:
- Journal Name: Monthly Notices of the Royal Astronomical Society; Journal ID: ISSN 0035-8711
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ATOMS; CONVERGENCE; MASS DISTRIBUTION; PROBABILITY; SAMPLING; SKY; GRAVITATIONAL LENSES; Astrophysics,ASTRO
Citation Formats
Marshall, Phil, and /KIPAC, Menlo Park. Atomic Inference from Weak Gravitational Lensing Data. United States: N. p., 2005.
Web.
Marshall, Phil, & /KIPAC, Menlo Park. Atomic Inference from Weak Gravitational Lensing Data. United States.
Marshall, Phil, and /KIPAC, Menlo Park. 2005.
"Atomic Inference from Weak Gravitational Lensing Data". United States. https://www.osti.gov/servlets/purl/877491.
@article{osti_877491,
title = {Atomic Inference from Weak Gravitational Lensing Data},
author = {Marshall, Phil and /KIPAC, Menlo Park},
abstractNote = {We present a novel approach to reconstructing the projected mass distribution from the sparse and noisy weak gravitational lensing shear data. The reconstructions are regularized via the knowledge gained from numerical simulations of clusters, with trial mass distributions constructed from n NFW profile ellipsoidal components. The parameters of these ''atoms'' are distributed a priori as in the simulated clusters. Sampling the mass distributions from the atom parameter probability density function allows estimates of the properties of the mass distribution to be generated, with error bars. The appropriate number of atoms is inferred from the data itself via the Bayesian evidence, and is typically found to be small, reecting the quality of the data. Ensemble average mass maps are found to be robust to the details of the noise realization, and succeed in recovering the demonstration input mass distribution (from a realistic simulated cluster) over a wide range of scales. As an application of such a reliable mapping algorithm, we comment on the residuals of the reconstruction and the implications for predicting convergence and shear at specific points on the sky.},
doi = {},
url = {https://www.osti.gov/biblio/877491},
journal = {Monthly Notices of the Royal Astronomical Society},
issn = {0035-8711},
number = ,
volume = ,
place = {United States},
year = {Wed Dec 14 00:00:00 EST 2005},
month = {Wed Dec 14 00:00:00 EST 2005}
}
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