Elucidating Galaxy Population Properties Using a Model-Free Analysis of Quadruply Imaged Quasar Lenses From Large Surveys
John Miller Jr, Liliya L. R. Williams

TL;DR
This paper introduces a model-free method to analyze quadruply imaged quasar lenses, enabling the empirical study of galaxy population properties without fitting individual mass models, which is crucial for upcoming large survey data.
Contribution
It presents a novel, model-free approach linking observable quad image properties to underlying galaxy population characteristics, bypassing traditional mass modeling.
Findings
Established a relation between image property space and galaxy property space.
Demonstrated the method using mock galaxy populations and quads.
Enabled estimation of galaxy population properties from quad observations.
Abstract
The population of strong lensing galaxies is a sub-set of intermediate-redshift massive galaxies, whose population-level properties are not yet well understood. In the near future, thousands of multiply imaged systems are expected to be discovered by wide-field surveys like Rubin Observatory's Legacy Survey of Space and Time (LSST) and Euclid. With the soon-to-be robust population of quadruply lensed quasars, or quads, in mind, we introduce a novel technique to elucidate the empirical distribution of the galaxy population properties. Our re-imagining of the prevailing strong lensing analysis does not fit mass models to individual lenses, but instead starts with parametric models of many galaxy populations, which include generally ignored mass distribution complexities and exclude external shear for now. We construct many mock galaxy populations with different properties and obtain…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAstronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena · Advanced Statistical Methods and Models
