SIMBAD references

2022MNRAS.514.2855P - Mon. Not. R. Astron. Soc., 514, 2855-2863 (2022/August-1)

Lensing in the darkness: a Bayesian analysis of 22 Chandra sources at z >= 6 shows no evidence of lensing.

PACUCCI F., FOORD A., GORDON L. and LOEB A.

Abstract (from CDS):

More than 200 quasars have been detected so far at z > 6, with only one showing clear signs of strong gravitational lensing. Some studies call for a missing population of lensed high-z quasars, but their existence is still in doubt. A large fraction of high-z quasars being lensed would have a significant effect on the shape of the intrinsic quasar luminosity function (QLF). Here, we perform the first systematic search for lensed X-ray-detected quasars at z >= 6 employing a Bayesian analysis, with the code BAYMAX, to look for morphological evidence of multiple images that may escape a visual inspection. We analysed a sample of 22 quasars at z > 5.8 imaged by the Chandra X-ray observatory and found none with statistically significant multiple images. In the sub-sample of the eight sources with photon counts >20, we exclude multiple images with separations r > 1 arcsec and count ratios f > 0.4, or with separations as small as 0.7 arcsec and f > 0.7 at 95 per cent confidence level. Comparing this non-detection with predictions from theoretical models suggesting a high- and a low-lensed fraction, we placed upper limits on the bright-end slope, β, of the QLF. Using only the sub-sample with eight sources, we obtain, in the high-lensing model, a limit β < 3.38. Assuming no multiple source is present in the full sample of 22 sources, we obtain β < 2.89 and β < 3.53 in the high- and low-lensing models, respectively. These constraints strongly disfavour steep QLF shapes previously proposed in the literature.

Abstract Copyright: © 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society

Journal keyword(s): gravitational lensing: strong - methods: statistical - surveys - quasars: supermassive black holes - X-rays: general

Simbad objects: 23

goto Full paper

goto View the references in ADS

To bookmark this query, right click on this link: simbad:2022MNRAS.514.2855P and select 'bookmark this link' or equivalent in the popup menu