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August 9, 2016Journal of Cosmology and Astroparticle Physics117 citationsOpen Access

The mass-sheet degeneracy and time-delay cosmography: analysis of the strong lens RXJ1131-1231

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SBSimon BirrerAAA. AmaraARAlexandre Réfrégier

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Abstract

We present extended modeling of the strong lens system RXJ1131-1231 with archival data in two HST bands in combination with existing line-of-sight contribution and velocity dispersion estimates. Our focus is on source size and its influence on time-delay cosmography. We therefore examine the impact of mass-sheet degeneracy and especially the degeneracy pointed out by Schneider & Sluse (2013) using the source reconstruction scale. We also extend on previous work by further exploring the effects of priors on the kinematics of the lens and the external convergence in the environment of the lensing system. Our results coming from RXJ1131-1231 are given in a simple analytic form so that they can be easily combined with constraints coming from other cosmological probes. We find that the choice of priors on lens model parameters and source size are subdominant for the statistical errors for H₀ measurements of this systems. The choice of prior for the source is sub-dominant at present (2% uncertainty on H₀) but may be relevant for future studies. More importantly, we find that the priors on the kinematic anisotropy of the lens galaxy have a significant impact on our cosmological inference. When incorporating all the above modeling uncertainties, we find H₀ = 86. 6^+6. 8-₆. ₉ km s^-1Mpc^-1, when using kinematic priors similar to other studies. When we use a different kinematic prior motivated by Barnab\`e et al. (2012) but covering the same anisotropic range, we find H₀ = 74. 5^+8. 0-₇. ₈ km s^-1Mpc^-1. This means that the choice of kinematic modeling and priors have a significant impact on cosmographic inferences. The way forward is either to get better velocity dispersion measures which would down weight the impact of the priors or to construct physically motivated priors for the velocity dispersion model.

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Birrer et al. (2016) studied this question.

synapsesocial.com/papers/6a15d9dbcaf7e3ea0ee3c6d8https://doi.org/10.1088/1475-7516/2016/08/020
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