SIMBAD references

2014ApJ...788L..35S - Astrophys. J., 788, L35 (2014/June-3)

Cosmology from gravitational lens time delays and Planck data.

SUYU S.H., TREU T., HILBERT S., SONNENFELD A., AUGER M.W., BLANDFORD R.D., COLLETT T., COURBIN F., FASSNACHT C.D., KOOPMANS L.V.E., MARSHALL P.J., MEYLAN G., SPINIELLO C. and TEWES M.

Abstract (from CDS):

Under the assumption of a flat ΛCDM cosmology, recent data from the Planck satellite point toward a Hubble constant that is in tension with that measured by gravitational lens time delays and by the local distance ladder. Prosaically, this difference could arise from unknown systematic uncertainties in some of the measurements. More interestingly–if systematics were ruled out–resolving the tension would require a departure from the flat ΛCDM cosmology, introducing, for example, a modest amount of spatial curvature, or a non-trivial dark energy equation of state. To begin to address these issues, we present an analysis of the gravitational lens RXJ1131-1231 that is improved in one particular regard: we examine the issue of systematic error introduced by an assumed lens model density profile. We use more flexible gravitational lens models with baryonic and dark matter components, and find that the exquisite Hubble Space Telescope image with thousands of intensity pixels in the Einstein ring and the stellar velocity dispersion of the lens contain sufficient information to constrain these more flexible models. The total uncertainty on the time-delay distance is 6.6% for a single system. We proceed to combine our improved time-delay distance measurement with the WMAP9 and Planck posteriors. In an open ΛCDM model, the data for RXJ1131-1231 in combination with Planck favor a flat universe with Ωk = 0.00–0.02+0.01 (68% credible interval (CI)). In a flat wCDM model, the combination of RXJ1131-1231 and Planck yields ω= -1.52–0.20+0.19 (68% CI).

Abstract Copyright:

Journal keyword(s): distance scale - galaxies: individual: RXJ1131-1231 - gravitational lensing: strong - methods: data analysis

Simbad objects: 2

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