TL;DR
This paper develops a formalism for analyzing complete samples of strong gravitational lenses, enabling unbiased inference of galaxy population properties and improved constraints on galaxy structure models.
Contribution
It introduces a general statistical framework for analyzing complete lens samples with known selection functions, tested on simulated data.
Findings
The method accurately recovers the distribution of Einstein radii and mass density slopes.
Non-lens data helps constrain galaxy models without magnification information.
Complete lens samples enhance understanding of the general galaxy population.
Abstract
Context. Existing samples of strong lenses have been assembled by giving priority to sample size, at the cost of having a complex selection function. With the advent of the next generation of wide-field photometric surveys, however, it might become possible to identify subsets of the lens population with well-defined selection criteria, trading sample size for completeness. Aims. There are two main advantages of working with a complete sample of lenses. First, it is possible to recover the properties of the general population of galaxies, of which strong lenses are a biased subset. Second, the relative number of lenses and non-detections can be used to further constrain models of galaxy structure. This work illustrates how to carry out a statistical strong lensing analysis that takes advantage of these features. Methods. I introduced a general formalism for the statistical analysis…
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