Journal
GENERAL RELATIVITY AND GRAVITATION
Volume 42, Issue 9, Pages 2151-2176Publisher
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10714-010-1041-1
Keywords
Strong gravitational lensing; Lens modeling; Galaxy structure; Statistical methods
Funding
- NSF [AST-0747311]
- Direct For Mathematical & Physical Scien [0747311] Funding Source: National Science Foundation
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I review methods for modeling gravitational lens systems comprising multiple images of a background source surrounding a foreground galaxy. In a Bayesian framework, the likelihood is driven by the nature of the data, which in turn depends on whether the source is point-like or extended. The prior encodes astrophysical expectations about lens galaxy mass distributions, either through a careful choice of model families, or through an explicit Bayesian prior applied to under-constrained free-form models. We can think about different lens modeling methods in terms of their choices of likelihoods and priors.
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