J.W. Nightingale
AutoLens: automated modeling of a strong lens's light, mass, and source
Nightingale, J.W.; Dye, S.; Massey, R.J.
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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