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A new strategy for matching observed and simulated lensing galaxies


Denzel, Philipp; Mukherjee, Sampath; Saha, Prasenjit (2021). A new strategy for matching observed and simulated lensing galaxies. Monthly Notices of the Royal Astronomical Society, 506(2):1815-1831.

Abstract

The study of strong-lensing systems conventionally involves constructing a mass distribution that can reproduce the observed multiply imaging properties. Such mass reconstructions are generically non-unique. Here, we present an alternative strategy: instead of modelling the mass distribution, we search cosmological galaxy-formation simulations for plausible matches. In this paper, we test the idea on seven well-studied lenses from the SLACS survey. For each of these, we first pre-select a few hundred galaxies from the EAGLE simulations, using the expected Einstein radius as an initial criterion. Then, for each of these pre-selected galaxies, we fit for the source light distribution, while using MCMC optimization for the placement and orientation of the lensing galaxy, so as to reproduce the multiple images and arcs. The results indicate that the strategy is feasible and can easily reject unphysical galaxy-formation scenarios. It even yields relative posterior probabilities of two different galaxy-formation scenarios, though these are not statistically significant yet. Extensions to other observables, such as kinematics and colours of the stellar population in the lensing galaxy, are straightforward in principle, though we have not attempted it yet. Scaling to arbitrarily large numbers of lenses also appears feasible. This will be especially relevant for upcoming wide-field surveys, through which the number of galaxy lenses will rise possibly a hundredfold, which will overwhelm conventional modelling methods.

Abstract

The study of strong-lensing systems conventionally involves constructing a mass distribution that can reproduce the observed multiply imaging properties. Such mass reconstructions are generically non-unique. Here, we present an alternative strategy: instead of modelling the mass distribution, we search cosmological galaxy-formation simulations for plausible matches. In this paper, we test the idea on seven well-studied lenses from the SLACS survey. For each of these, we first pre-select a few hundred galaxies from the EAGLE simulations, using the expected Einstein radius as an initial criterion. Then, for each of these pre-selected galaxies, we fit for the source light distribution, while using MCMC optimization for the placement and orientation of the lensing galaxy, so as to reproduce the multiple images and arcs. The results indicate that the strategy is feasible and can easily reject unphysical galaxy-formation scenarios. It even yields relative posterior probabilities of two different galaxy-formation scenarios, though these are not statistically significant yet. Extensions to other observables, such as kinematics and colours of the stellar population in the lensing galaxy, are straightforward in principle, though we have not attempted it yet. Scaling to arbitrarily large numbers of lenses also appears feasible. This will be especially relevant for upcoming wide-field surveys, through which the number of galaxy lenses will rise possibly a hundredfold, which will overwhelm conventional modelling methods.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Physics Institute
Dewey Decimal Classification:530 Physics
Scopus Subject Areas:Physical Sciences > Astronomy and Astrophysics
Physical Sciences > Space and Planetary Science
Uncontrolled Keywords:Space and Planetary Science, Astronomy and Astrophysics
Language:English
Date:16 July 2021
Deposited On:17 Jan 2022 09:22
Last Modified:26 Jun 2024 01:49
Publisher:Oxford University Press
ISSN:0035-8711
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/mnras/stab1716
Project Information:
  • : FunderSwiss National Science Foundation
  • : Grant ID
  • : Project Title
  • : FunderEuropean Research Council
  • : Grant ID
  • : Project Title
  • : FunderH2020
  • : Grant ID787886
  • : Project TitleCOSMICLENS - Cosmology with Strong Gravitational Lensing
  • Content: Published Version
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)