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Galaxy mass profiles from strong lensing II: The elliptical power-law model
Stockholm University, Faculty of Science, Department of Astronomy. Imperial College London, UK.
Number of Authors: 32020 (English)In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 496, no 3, p. 3424-3435Article in journal (Refereed) Published
Abstract [en]

We present a systematic analysis of the constraints σγ on the mass profile slope γ obtainable when fitting a singular power-law ellipsoid model to a typical strong lensing observation of an extended source. These results extend our previous analysis of circular systems, Paper I. We draw our results from 676 mock observations covering a range of image configurations, each created with a fixed signal to noise ratio S = 100 in the images. We analyse the results using a combination of theory and a simplified model which identifies the contribution to the constraints of the individual fluxes and positions in each of the lensed images. The main results are: 1. For any lens ellipticity, the constraints σγ for two image systems are well described by the results of Paper I, transformed to elliptical coordinates; 2. We derive an analytical expression for σγ for systems with the source aligned with the axis of the lens; 3. For both two-image systems and aligned systems, σγ is limited by the flux uncertainties; 4. The constraints for off-axis four-image systems are a factor of two to eight better, depending on source size, than for two-image systems, and improve with increasing lens ellipticity. We show that the constraints on γ in these systems derive from the complementary positional information of the images alone, without using flux. The complementarity improves as the offset of the source from the axis increases, such that the best constraints σγ < 0.01, for S = 100, occur when the source approaches the caustic.

Place, publisher, year, edition, pages
2020. Vol. 496, no 3, p. 3424-3435
Keywords [en]
gravitational lensing: strong
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:su:diva-186698DOI: 10.1093/mnras/staa1697ISI: 000574919300051OAI: oai:DiVA.org:su-186698DiVA, id: diva2:1501564
Available from: 2020-11-17 Created: 2020-11-17 Last updated: 2022-02-25Bibliographically approved

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Mortlock, Daniel J.

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