A Survey for Large–Image Separation Lensed Quasars
Open Access
- 1 September 1997
- journal article
- research article
- Published by American Astronomical Society in The Astrophysical Journal
- Vol. 486 (1) , 75-84
- https://doi.org/10.1086/304503
Abstract
The statistics of gravitationally lensed quasars with multiple images in the 01-7'' range have been measured in various surveys. Little is known, however, about lensed-quasar statistics at larger image separations, which probe masses on the scale of galaxy clusters. We extend the results of the Hubble Space Telescope (HST) Snapshot Survey for Lensed Quasars to the 7''-50'' range for a subsample of 76 quasars that is free of known selection effects. Using a combination of multicolor photometry and spectroscopy, we show that none of the point sources in the entire field of view of the HST observations of these quasars are lensed images. Large-separation quasar lensing is therefore not common. We carry out a detailed calculation of the expected statistics of large-separation lensing for this quasar sample, incorporating realistic input for the mass profiles and mass function of galaxy clusters. We find that the observational null results are consistent with the expected effect of galaxy clusters, even if these have existed in their present form and number since z ~ 2 (and certainly if they were formed more recently). The rarity of large-separation lensed quasars can rule out some extreme scenarios, e.g., that the mass function of clusters has been severely underestimated or that large mass concentrations that are not associated with galaxies (i.e., "failed" clusters) are common. The rareness of cluster lensing also sets limits on the cosmological constant λ that are independent of limits derived from galaxy lensing. The lensing frequency depends strongly on the central density of clusters. The lensing statistics of larger quasar samples (e.g., the Sloan Digital Sky Survey) can probe the structure, number, and evolution of clusters, as well as the geometry of space.Keywords
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