On modeling galaxy-scale strong lens systems

Astronomy and Astrophysics – Astrophysics

Scientific paper

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Strong Gravitational Lensing, Lens Modeling, Galaxy Structure, Statistical Methods

Scientific paper

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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