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AutoLens: automated modeling of a strong lens's light, mass, and source

Nightingale, J.W.; Dye, S.; Massey, R.J.

AutoLens: automated modeling of a strong lens's light, mass, and source Thumbnail


Authors

J.W. Nightingale

S. Dye



Abstract

This work presents AutoLens, the first entirely automated modeling suite for the analysis of galaxy-scale strong gravitational lenses. AutoLens simultaneously models the lens galaxy’s light and mass whilst reconstructing the extended source galaxy on an adaptive pixel-grid. The method’s approach to source-plane discretization is amorphous, adapting its clustering and regularization to the intrinsic properties of the lensed source. The lens’s light is fitted using a superposition of Sersic functions, allowing AutoLens to cleanly deblend its light from the source. Single-component mass models representing the lens’s total mass density profile are demonstrated, which in conjunction with light modeling can detect central images using a centrally cored profile. Decomposed mass modeling is also shown, which can fully decouple a lens’s light and dark matter and determine whether the two components are geometrically aligned. The complexity of the light and mass models is automatically chosen via Bayesian model comparison. These steps form AutoLens’s automated analysis pipeline, such that all results in this work are generated without any user intervention. This is rigorously tested on a large suite of simulated images, assessing its performance on a broad range of lens profiles, source morphologies, and lensing geometries. The method’s performance is excellent, with accurate light, mass, and source profiles inferred for data sets representative of both existing Hubble imaging and future Euclid wide-field observations.

Citation

Nightingale, J., Dye, S., & Massey, R. (2018). AutoLens: automated modeling of a strong lens's light, mass, and source. Monthly Notices of the Royal Astronomical Society, 478(4), 4738-4784. https://doi.org/10.1093/mnras/sty1264

Journal Article Type Article
Acceptance Date May 3, 2018
Online Publication Date May 22, 2018
Publication Date May 22, 2018
Deposit Date Jul 11, 2018
Publicly Available Date Mar 29, 2024
Journal Monthly Notices of the Royal Astronomical Society
Print ISSN 0035-8711
Electronic ISSN 1365-2966
Publisher Royal Astronomical Society
Peer Reviewed Peer Reviewed
Volume 478
Issue 4
Pages 4738-4784
DOI https://doi.org/10.1093/mnras/sty1264

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Copyright Statement
This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society © 2018 The Authors.
Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.





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