A Catalog of Candidate Double and Lensed Quasars from Gaia and WISE Data
| Autor: | Nathan Secrest, Valeri Makarov |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | The Astrophysical Journal Supplement Series. 264:4 |
| ISSN: | 1538-4365 0067-0049 |
| DOI: | 10.3847/1538-4365/ac97f0 |
| Popis: | Making use of strong correlations between closely separated multiple or double sources and photometric and astrometric metadata in Gaia EDR3, we generate a catalog of candidate double and multiply imaged lensed quasars and AGNs, comprising 3140 systems. It includes two partially overlapping parts, a sample of distant (redshifts mostly greater than 1) sources with perturbed data, and systems resolved into separate components by Gaia at separations less than $2\arcsec$. For the first part, which is roughly one third of the published catalog, we synthesized 0.617 million redshifts by multiple machine learning prediction and classification methods, using independent photometric and astrometric data from Gaia EDR3 and WISE with accurate spectroscopic redshifts from SDSS as a training set. Using these synthetic redshifts, we estimate a rate of 4.9\% of interlopers with spectroscopic redshift below 1 in this part of the catalog. Unresolved candidate double and dual AGNs and quasars are selected as sources with marginally high BP/RP excess factor (phot_bp_rp_excess_factor), which is sensitive to source extent, limiting our search to high-redshift quasars. For the second part of the catalog, additional filters on measured parallax and near-neighbor statistics are applied to diminish the propagation of remaining stellar contaminants. The estimated rate of positives (double or multiple sources) is 98\%, and the estimated rate of dual (physically related quasars) is greater than 54\%. A few dozen serendipitously found objects of interest are discussed in more detail, including known and new lensed images, planetary nebulae and young infrared stars of peculiar morphology, and quasars with catastrophic redshift errors in SDSS. Accepted in ApJS |
| Databáze: | OpenAIRE |
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