Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/31220
Title: Free-form GRALE lens inversion of galaxy clusters with up to 1000 multiple images
Authors: Ghosh, Agniva
Williams, Liliya L.R.
LIESENBORGS, Jori 
Issue Date: 2020
Publisher: 
Source: MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 494 (3) , p. 3998 -4014
Abstract: In the near future, ultra deep observations of galaxy clusters with Hubble Space Telescope or James Webb Space Telescope will uncover 300–1000 lensed multiple images, increasing the current count per cluster by up to an order of magnitude. This will further refine our view of clusters, leading to a more accurate and precise mapping of the total and dark matter distribution in clusters, and enabling a better understanding of background galaxy population and their luminosity functions. However, to effectively use that many images as input to lens inversion will require a re-evaluation of, and possibly upgrades to the existing methods. In this paper, we scrutinize the performance of the free-form lens inversion method GRALE in the regime of 150–1000 input images, using synthetic massive galaxy clusters. Our results show that with an increasing number of input images, GRALE produces improved reconstructed mass distributions, with the fraction of the lens plane recovered at better than 10 per cent accuracy increasing from 40−50 per cent for ∼150 images to 65 per cent for ∼1000 images. The reconstructed time delays imply a more precise measurement of H0, with ≲1 per cent bias. While the fidelity of the reconstruction improves with the increasing number of multiple images used as model constraints, ∼150 to ∼1000, the lens plane rms deteriorates from ∼0.11 to ∼0.28 arcsec. Since lens plane rms is not necessarily the best indicator of the quality of the mass reconstructions, looking for an alternative indicator is warranted.
Keywords: gravitational lensing: strong;galaxies: clusters: general
Document URI: http://hdl.handle.net/1942/31220
ISSN: 0035-8711
e-ISSN: 1365-2966
DOI: 10.1093/mnras/staa962
ISI #: WOS:000535882100070
Rights: 2020 The Author(s)
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
2004.01724.pdfNon Peer-reviewed author version12.91 MBAdobe PDFView/Open
Show full item record

WEB OF SCIENCETM
Citations

16
checked on Apr 23, 2024

Page view(s)

80
checked on Sep 7, 2022

Download(s)

4
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.