AutoLens: Automated Modeling of a Strong Lens's Light, Mass and Source
James Nightingale Simon Dye Richard Massey


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firstpage–lastpage 
2018
Maximum redshift of  gravitational wave merger events
    Abraham Loeb
    
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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 component are geometrically aligned. The complexity of the light and mass models are 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.  



gravitational lensing - galaxies: structure


1_Introduction.tex
2a_Overview.tex
2_Simulations.tex
3_AutoLens.tex
3a_Demonstration.tex
4_Pipeline.tex
5_Results.tex
6_Discussion.tex



§ ACKNOWLEDGEMENTS


JN acknowledges support from STFC grant ST/N00149/1 and the University of Nottingham. SD acknowledges support from the Midlands Physics Alliance and STFC Ernest Rutherford Fellowship Scheme. RJM acknowledges support from the Royal Society University Research Fellowship. We are grateful for access to the University of Nottingham High Performance Computing Facility. This paper used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). This equipment was funded by BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grant ST/H008519/1, and STFC DiRAC Operations grant ST/K003267/1 and Durham University. DiRAC is part of the National e-Infrastructure. We acknowledge use of the software program (getdist.readthedocs.io/en/latest/).

Appendices.tex

            



