Show simple item record

dc.contributor.authorYang, Qian*
dc.contributor.authorWu, Xue-Bing*
dc.contributor.authorFan, Xiaohui*
dc.contributor.authorJiang, Linhua*
dc.contributor.authorMcGreer, Ian D.*
dc.contributor.authorGreen, Richard*
dc.contributor.authorYang, Jinyi*
dc.contributor.authorSchindler, Jan-Torge*
dc.contributor.authorWang, Feige*
dc.contributor.authorZuo, Wenwen*
dc.contributor.authorFu, Yuming*
dc.date.accessioned2018-03-22T21:07:25Z
dc.date.available2018-03-22T21:07:25Z
dc.date.issued2017-12-01
dc.identifier.citationQuasar Photometric Redshifts and Candidate Selection: A New Algorithm Based on Optical and Mid-infrared Photometric Data 2017, 154 (6):269 The Astronomical Journalen
dc.identifier.issn1538-3881
dc.identifier.doi10.3847/1538-3881/aa943c
dc.identifier.urihttp://hdl.handle.net/10150/627092
dc.description.abstractWe present a new algorithm to estimate quasar photometric redshifts (photo-zs), by considering the asymmetries in the relative flux distributions of quasars. The relative flux models are built with multivariate Skew-t distributions in the multidimensional space of relative fluxes as a function of redshift and magnitude. For 151,392 quasars in the SDSS, we achieve a photo-z accuracy, defined as the fraction of quasars with the difference between the photo-z z(p) and the spectroscopic redshift z(s), vertical bar Delta z vertical bar=vertical bar z(s)-z(p)vertical bar/(1 + z(s)) within 0.1, of 74%. Combining the WISE W1 and W2 infrared data with the SDSS data, the photo-z accuracy is enhanced to 87%. Using the Pan-STARRS1 or DECaLS photometry with WISE W1 and W2 data, the photo-z accuracies are 79% and 72%, respectively. The prior probabilities as a function of magnitude for quasars, stars, and galaxies are calculated, respectively, based on (1) the quasar luminosity function, (2) the Milky Way synthetic simulation with the Besancon model, and (3) the Bayesian Galaxy Photometric Redshift estimation. The relative fluxes of stars are obtained with the Padova isochrones, and the relative fluxes of galaxies are modeled through galaxy templates. We test our classification method to select quasars using the DECaLS g, r, z, and WISE W1 and W2 photometry. The quasar selection completeness is higher than 70% for a wide redshift range 0.5 < z < 4.5, and a wide magnitude range 18 < r < 21.5 mag. Our photo-z regression and classification method has the potential to extend to future surveys. The photo-z code will be publicly available.
dc.description.sponsorshipMinistry of Science and Technology of China [2016YFA0400703]; NSFC [11373008, 11533001]; National Key Basic Research Program of China [2014CB845700]; Alfred P. Sloan Foundation; National Science Foundation; U.S. Department of Energy Office of Science; University of Arizona; Brazilian Participation Group; Brookhaven National Laboratory; Carnegie Mellon University; University of Florida; French Participation Group; German Participation Group; Harvard University; Instituto de Astrofisica de Canarias; Michigan State/Notre Dame/JINA Participation Group; Johns Hopkins University; Lawrence Berkeley National Laboratory; Max Planck Institute for Astrophysics; Max Planck Institute for Extraterrestrial Physics; New Mexico State University; New York University; Ohio State University; Pennsylvania State University; University of Portsmouth; Princeton University; Spanish Participation Group; University of Tokyo; University of Utah; Vanderbilt University; University of Virginia; University of Washington; Yale University; National Aeronautics and Space Administration [NNX08AR22G]; National Science Foundation [AST-1238877]; National Aeronautics and Space Administrationen
dc.language.isoenen
dc.publisherIOP PUBLISHING LTDen
dc.relation.urlhttp://stacks.iop.org/1538-3881/154/i=6/a=269?key=crossref.47a921b83fc023b8aaf10860e08d557fen
dc.rights© 2017. The American Astronomical Society. All rights reserved.en
dc.subjectcatalogsen
dc.subjectcosmology: observationsen
dc.subjectgalaxies: distances and redshiftsen
dc.subjectmethods: statisticalen
dc.subjectquasars: generalen
dc.titleQuasar Photometric Redshifts and Candidate Selection: A New Algorithm Based on Optical and Mid-infrared Photometric Dataen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Steward Observen
dc.identifier.journalThe Astronomical Journalen
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-06-12T00:14:30Z
html.description.abstractWe present a new algorithm to estimate quasar photometric redshifts (photo-zs), by considering the asymmetries in the relative flux distributions of quasars. The relative flux models are built with multivariate Skew-t distributions in the multidimensional space of relative fluxes as a function of redshift and magnitude. For 151,392 quasars in the SDSS, we achieve a photo-z accuracy, defined as the fraction of quasars with the difference between the photo-z z(p) and the spectroscopic redshift z(s), vertical bar Delta z vertical bar=vertical bar z(s)-z(p)vertical bar/(1 + z(s)) within 0.1, of 74%. Combining the WISE W1 and W2 infrared data with the SDSS data, the photo-z accuracy is enhanced to 87%. Using the Pan-STARRS1 or DECaLS photometry with WISE W1 and W2 data, the photo-z accuracies are 79% and 72%, respectively. The prior probabilities as a function of magnitude for quasars, stars, and galaxies are calculated, respectively, based on (1) the quasar luminosity function, (2) the Milky Way synthetic simulation with the Besancon model, and (3) the Bayesian Galaxy Photometric Redshift estimation. The relative fluxes of stars are obtained with the Padova isochrones, and the relative fluxes of galaxies are modeled through galaxy templates. We test our classification method to select quasars using the DECaLS g, r, z, and WISE W1 and W2 photometry. The quasar selection completeness is higher than 70% for a wide redshift range 0.5 < z < 4.5, and a wide magnitude range 18 < r < 21.5 mag. Our photo-z regression and classification method has the potential to extend to future surveys. The photo-z code will be publicly available.


Files in this item

Thumbnail
Name:
Yang_2017_AJ_154_269.pdf
Size:
2.821Mb
Format:
PDF
Description:
Final Published Version

This item appears in the following Collection(s)

Show simple item record