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Oxford University Press, Monthly Notices of the Royal Astronomical Society, 3(502), p. 4617-4640, 2021

DOI: 10.1093/mnras/stab267

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The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: A Catalogue of Strong Galaxy-Galaxy Lens Candidates

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

ABSTRACT We spectroscopically detected 838 likely, 448 probable, and 265 possible strong lens candidates within ≈2 million galaxy spectra contained within the extended Baryon Oscillation Spectroscopic Survey (eBOSS) from the sixteenth data release (DR16) of the Sloan Digital Sky Survey (SDSS). We apply the spectroscopic detection method of the Baryon Oscillation Spectroscopic Survey (BOSS) Emission-Line Lens Survey (BELLS) and add Gaussian fit information, grading, additional inspection observables, and additional inspection methods to improve our selection method. We observed 477 candidates with lensing evidence within low-resolution images from both the Legacy survey of SDSS-I/II and the DESI Legacy survey, which is $12{{\ \rm per\ cent}}$ higher than the percentage of BELLS candidates observed with similar lensing evidence. Our search within the latest and improved reductions of the BOSS survey yielded a $20{{\ \rm per\ cent}}$ increase in the number of lens candidates expected from searching all BOSS and eBOSS galaxies. The distribution of target and background redshifts of our candidates is similar to the candidates and confirmed lenses within the BELLS observations. We present our Spectroscopic Identification of Lensing Object candidates in a value-added catalogue in SDSS DR16. The examination of these lens candidates in follow-up high-resolution imaging may yield more than twice the lenses found in previous spectroscopic detection surveys within SDSS, which would extend the results of previous lens surveys within SDSS to higher redshifts, constrain models of mass structures in spiral galaxies, and test if including the identification of possible lensing features within low-resolution images has merit to spectroscopic detection programmes.