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<ri:Resource created="2021-12-14T08:37:38Z" status="active" updated="2025-05-19T09:50:00Z" version="1.2" xmlns:cs="http://www.ivoa.net/xml/ConeSearch/v1.0" xmlns:ri="http://www.ivoa.net/xml/RegistryInterface/v1.0" xmlns:vr="http://www.ivoa.net/xml/VOResource/v1.0" xmlns:vs="http://www.ivoa.net/xml/VODataService/v1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ivoa.net/xml/ConeSearch/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/ConeSearch.xsd http://www.ivoa.net/xml/VOResource/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/VOResource.xsd http://www.ivoa.net/xml/VODataService/v1.1 http://vo.ari.uni-heidelberg.de/docs/schemata/VODataService.xsd" xsi:type="vs:CatalogService"><title>Random forests method to discover high-redshift QSOs</title><shortName>J/AJ/162/72</shortName><identifier>ivo://CDS.VizieR/J/AJ/162/72</identifier><altIdentifier>doi:10.26093/cds/vizier.51620072</altIdentifier><curation><publisher ivo-id="ivo://CDS">CDS</publisher><creator><name>Wenzl L.</name></creator><creator><name>Schindler J.-T.</name></creator><creator><name>Fan X.</name></creator><creator><name>Andika I.T.</name></creator><creator><name>Banados E.</name></creator><creator><name>Decarli R.,Jahnke K.</name></creator><creator><name>Mazzucchelli C.</name></creator><creator><name>Onoue M.</name></creator><creator><name>Venemans B.P.</name></creator><creator><name>Walter F.</name></creator><creator><name>Yang J.</name></creator><date role="Updated">2022-03-14T07:01:17Z</date><date role="Created">2021-12-14T08:37:38Z</date><contact><name>CDS support team</name><address>CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France</address><email>cds-question@unistra.fr</email></contact></curation><content><subject>quasars</subject><subject>active-galactic-nuclei</subject><subject>black-holes</subject><subject>redshifted</subject><subject>visible-astronomy</subject><subject>spectroscopy</subject><subject>infrared-astronomy</subject><description>We present a method of selecting quasars up to redshift ~6 with random forests, a supervised machine-learning method, applied to Pan-STARRS1 and WISE data. We find that, thanks to the increasing set of known quasars, we can assemble a training set that enables supervised machine-learning algorithms to become a competitive alternative to other methods up to this redshift. We present a candidate set for the redshift range 4.8-6.3, which includes the region around z=5.5 where selecting quasars is difficult due to their photometric similarity to red and brown dwarfs. We demonstrate that, under our survey restrictions, we can reach a high completeness (66%{+/-}7% below redshift 5.6/83_-9_^+6^% above redshift 5.6) while maintaining a high selection efficiency (78_-8_^+10^%/94_-8_^+5^% ). Our selection efficiency is estimated via a novel method based on the different distributions of quasars and contaminants on the sky. The final catalog of 515 candidates includes 225 known quasars. We predict the candidate catalog to contain additional 148_-33_^+41^ new quasars below redshift 5.6 and 45_-8_^+5^ above, and we make the catalog publicly available. Spectroscopic follow-up observations of 37 candidates led us to discover 20 new high redshift quasars (18 at 4.6&lt;~z&lt;~5.5, 2z~5.7). These observations are consistent with our predictions on efficiency. We argue that random forests can lead to higher completeness because our candidate set contains a number of objects that would be rejected by common color cuts, including one of the newly discovered redshift 5.7 quasars.</description><source format="bibcode">2021AJ....162...72W</source><referenceURL>https://cdsarc.cds.unistra.fr/viz-bin/cat/J/AJ/162/72</referenceURL><type>Catalog</type><contentLevel>Research</contentLevel><relationship><relationshipType>IsServedBy</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/TAP">TAP VizieR generic service</relatedResource></relationship><relationship><relationshipType>IsServedBy</relationshipType><relatedResource>Conesearch service</relatedResource></relationship><relationship><relationshipType>related-to</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/VII/233">VII/233 : The 2MASS Extended sources (IPAC/UMass, 2003-2006)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/II/328">II/328 : AllWISE Data Release (Cutri+ 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/II/349">II/349 : The Pan-STARRS release 1 (PS1) Survey - DR1 (Chambers+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/VII/285">VII/285 : Gaia DR2 quasar and galaxy classification (Bailer-Jones+, 2019)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/VII/289">VII/289 : SDSS quasar catalog, sixteenth data release (DR16Q) (Lyke+, 2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/768/105">J/ApJ/768/105 : z~5 QSO luminosity function SDSS Stripe 82 (McGreer+, 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/773/14">J/ApJ/773/14 : BOSS: quasar luminosity function (Ross+, 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/819/24">J/ApJ/819/24 : z&gt;4.5 QSOs with SDSS and WISE. 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Opt. spectra (Wang+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/227/11">J/ApJS/227/11 : PS1 z&gt;5.6 quasars follow-up (Banados+, 2016)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/AJ/156/18">J/AJ/156/18 : APOGEE DR14:Bin companions evolved stars (Price-Whelan+, 2018)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/624/A13">J/A+A/624/A13 : KiDS DR3 QSO catalog (Nakoneczny+, 2019)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/632/A56">J/A+A/632/A56 : KiDS-BEXGO catalog (Khramtsov+, 2019)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/243/5">J/ApJS/243/5 : The ELQS in the PS1 footprint (PS-ELQS) (Schindler+, 2019)</relatedResource></relationship></content><rights>https://cds.unistra.fr/vizier-org/licences_vizier.html</rights><capability><interface xsi:type="vr:WebBrowser"><accessURL use="full">https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/AJ/162/72</accessURL><mirrorURL 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