Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/27470
Title: The role of multiple images and model priors in measuring H0 from supernova Refsdal in galaxy cluster MACS J1149.5+2223
Authors: Williams, Liliya L. R.
LIESENBORGS, Jori 
Issue Date: 2019
Publisher: OXFORD UNIV PRESS
Source: Monthly notices of the Royal Astronomical Society (Print), 482(4), p. 5666-5677
Abstract: Multiple image gravitational lensing systems with measured time delays provide a promising one-step method for determining H0. MACS J1149, which lenses SN Refsdal into a quad S1-S4, and two other widely separated images, SX and SY, is a perfect candidate. If time delays are pinned down, the remaining uncertainty arises from the mass distribution in the lens. In MACS J1149, the mass in the relevant lens plane region can be constrained by (i) many multiple images, (ii) the mass of the galaxy splitting S1-S4 (which, we show, is correlated with H0), (iii) magnification of SX (also correlated with H0), and (iv) prior assumptions on the mass distribution. Our goal is not to estimate H0, but to understand its error budget, i.e. estimate uncertainties associated with each of these constraints. Using multiple image positions alone yields very large uncertainty, despite the fact that the position of SX is recovered to within ≤0.036 arcsec (rms ≤ 0.36 arcsec) by GRALE lens inversion. Fixing the mass of the galaxy that splits S1-S4 reduces 1σ uncertainties to ∼23 per cent⁠, while fixing the magnification of SX yields 1σ uncertainties of 32 per cent⁠. We conclude that smaller uncertainties, of order few per cent, are a consequence of imposing prior assumptions on the shapes of the galaxy and cluster mass distributions, which may or may not apply in a highly non-equilibrium environment of a merging cluster. We propose that if a measurement of H0 is to be considered reliable, it must be supported by a wide range of lens inversion methods.
Keywords: gravitational lensing: strong; galaxies: clusters: individual: MACS J1149.5+2223; dark matter
Document URI: http://hdl.handle.net/1942/27470
ISSN: 0035-8711
e-ISSN: 1365-2966
DOI: 10.1093/mnras/sty3113
ISI #: WOS:000462327300105
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
Appears in Collections:Research publications

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