Home News About Us Contact Contributors Disclaimer Privacy Policy Help FAQ

Home
Search
Quick Search
Advanced
Fulltext
Browse
Collections
Persons
My eDoc
Session History
Login
Name:
Password:
Documentation
Help
Support Wiki
Direct access to
document ID:


          Institute: MPI für Astronomie     Collection: Publikationen_mpia     Display Documents



ID: 720032.0, MPI für Astronomie / Publikationen_mpia
Bayesian high-redshift quasar classification from optical and mid-IR photometry
Authors:Richards, G. T.; Myers, A. D.; Peters, C. M.; Krawczyk, C. M.; Chase, G.; Ross, N. P.; Fan, X.; Jiang, L.; Lacy, M.; McGreer, I. D.; Trump, J. R.; Riegel, R. N.
Date of Publication (YYYY-MM-DD):2015
Title of Journal:The Astrophysical Journal Supplement Series
Volume:219
Issue / Number:2
Start Page:id. 39 (21 pp)
Audience:Not Specified
Abstract / Description:We identify 885,503 type 1 quasar candidates to i≲ 22 using the combination of optical and mid-IR photometry. Optical photometry is taken from the Sloan Digital Sky Survey-III: Baryon Oscillation Spectroscopic Survey (SDSS-III/BOSS), while mid-IR photometry comes from a combination of data from the Wide-field Infrared Survey Explorer (WISE) “AllWISE” data release and several large-area Spitzer Space Telescope fields. Selection is based on a Bayesian kernel density algorithm with a training sample of 157,701 spectroscopically confirmed type 1 quasars with both optical and mid-IR data. Of the quasar candidates, 733,713 lack spectroscopic confirmation (and 305,623 are objects that we have not previously classified as photometric quasar candidates). These candidates include 7874 objects targeted as high-probability potential quasars with 3.5\lt z\lt 5 (of which 6779 are new photometric candidates). Our algorithm is more complete to z\gt 3.5 than the traditional mid-IR selection “wedges” and to 2.2\lt z\lt 3.5 quasars than the SDSS-III/BOSS project. Number counts and luminosity function analysis suggest that the resulting catalog is relatively complete to known quasars and is identifying new high-z quasars at z\gt 3. This catalog paves the way for luminosity-dependent clustering investigations of large numbers of faint, high-redshift quasars and for further machine-learning quasar selection using Spitzer and WISE data combined with other large-area optical imaging surveys.
Free Keywords:catalogs; infrared: galaxies; methods: statistical; quasars: general
External Publication Status:published
Document Type:Article
Communicated by:N. N.
Affiliations:MPI für Astronomie
Identifiers:ISSN:0067-0049
URL:http://cdsads.u-strasbg.fr/abs/2015ApJS..219...39R
The scope and number of records on eDoc is subject to the collection policies defined by each institute - see "info" button in the collection browse view.