Free-form grale lens inversion of galaxy clusters with up to 1000 multiple images

Agniva Ghosh, Liliya L.R. Williams, Jori Liesenborgs

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)3998-4014
Number of pages17
JournalMonthly Notices of the Royal Astronomical Society
Volume494
Issue number3
DOIs
StatePublished - 2020

Bibliographical note

Funding Information:
AG and LLRW acknowledge the Minnesota Supercomputing Institute (MSI) for their computational resources and support. We would like to thank the anonymous referee for their useful suggestions and comments.

Publisher Copyright:
© 2020 The Author(s).

Keywords

  • Galaxies: clusters: general
  • Gravitational lensing: strong

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