Reducing biases on H0 measurements using strong lensing and galaxy dynamics: results from the eagle simulation

Research output: Contribution to journalArticle

  • External authors:
  • Amitpal Singh Tagore
  • David Barnes
  • Matthieu Schaller
  • Joop Schaye
  • Tom Theuns

Abstract

Cosmological parameter constraints from observations of time-delay lenses are becoming increasingly precise. However, there may be significant bias and scatter in these measurements due to, among other things, the so-called mass-sheet degeneracy. To estimate these uncertainties, we analyze strong lenses from the largest eagle hydro- dynamical simulation. We apply a mass-sheet transformation to the radial density profiles of lenses, and by selecting lenses near isothermality, we find that the bias on H0 can be reduced to 5% with an intrinsic scatter of 10%, confirming previous results performed on a different simulation data set. We further investigate whether combining lensing observables with kinematic constraints helps to minimize this bias. We do not detect any significant dependence of the bias on lens model parameters or observational properties of the galaxy, but depending on the source–lens configuration, a bias may still exist. Cross lenses provide an accurate estimate of the Hubble constant, while fold (double) lenses tend to be biased low (high). With kinematic constraints, double lenses show bias and intrinsic scatter of 6% and 10%, respectively, while quad lenses show bias and intrinsic scatter of 0.5% and 10%, respectively. For lenses with a reduced ¬2 > 1, a power-law dependence of the ¬2 on the lens environment (number of nearby galaxies) is seen. Lastly, we model, in greater detail, the cases of two double lenses that are significantly biased. We are able to remove the bias, suggesting that the remaining biases could also be reduced by carefully taking into account additional sources of systematic uncertainty.

Bibliographical metadata

Original languageEnglish
JournalMonthly Notices of the Royal Astronomical Society
DOIs
StatePublished - 5 Dec 2017