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Lensing in the Darkness: A Bayesian Analysis of 22 Chandra Sources at $z \gtrsim 6$ Shows No Evidence of Lensing

Authors :
Pacucci, Fabio
Foord, Adi
Gordon, Lucia
Loeb, Abraham
Source :
Monthly Notices of the Royal Astronomical Society, 2022, Volume 514, Issue 2, pp.2855-2863
Publication Year :
2022

Abstract

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 $z \gtrsim 6$ employing a Bayesian analysis, with the code BAYMAX, to look for morphological evidence of multiple images that may escape a visual inspection. We analyzed 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 8 sources with photon counts $>20$ we exclude multiple images with separations $r>1''$ and count ratios $f>0.4$, or with separations as small as $0.''7$ and $f>0.7$ at $95\%$ 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, $\beta$, of the QLF. Using only the sub-sample with 8 sources, we obtain, in the high-lensing model, a limit $\beta < 3.38$. Assuming no multiple source is present in the full sample of 22 sources, we obtain $\beta < 2.89$ and $\beta < 3.53$ in the high and low lensing models, respectively. These constraints strongly disfavor steep QLF shapes previously proposed in the literature.<br />Comment: Accepted for publication in MNRAS. This is the final version of the manuscript. 10 pages, 5 figures

Details

Database :
arXiv
Journal :
Monthly Notices of the Royal Astronomical Society, 2022, Volume 514, Issue 2, pp.2855-2863
Publication Type :
Report
Accession number :
edsarx.2206.01217
Document Type :
Working Paper
Full Text :
https://doi.org/10.1093/mnras/stac1537