Finding New High-Redshift Quasars by Asking the Neighbours

Abstract

Quasars with a high redshift (z) are important to understand the evolution processes of galaxies in the early universe. However only a few of these distant objects are known to this date. The costs of building and operating a 10-metre class telescope limit the number of facilities and, thus, the available observation time. Therefore an efficient selection of candidates is mandatory. This paper presents a new approach to select quasar candidates with high redshift (z>4.8) based on photometric catalogues. We have chosen to use the z>4.8 limit for our approach because the dominant Lyman alpha emission line of a quasar can only be found in the Sloan i and z-band filters. As part of the candidate selection approach, a photometric redshift estimator is presented, too. Three of the 120,000 generated candidates have been spectroscopically analysed in follow-up observations and a new z=5.0 quasar was found. This result is consistent with the estimated detection ratio of about 50 per cent and we expect 60,000 high-redshift quasars to be part of our candidate sample. The created candidates are available for download at MNRAS or at http://www.astro.rub.de/polsterer/quasar-candidates.csv.

10 pages, 9 figures, accepted (MNRAS)

References in corpus (25)

• The Sloan Digital Sky Survey: Technical Summary
• Seven-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Interpretation
• Unified Schemes for Radio-Loud Active Galactic Nuclei
• The Host Galaxies of AGN
• Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Main Galaxy Sample
• The Sixth Data Release of the Sloan Digital Sky Survey
• Spectroscopic Target Selection for the Sloan Digital Sky Survey: The Luminous Red Galaxy Sample
• Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Quasar Sample
• The Sloan Digital Sky Survey Quasar Catalog V. Seventh Data Release
• A Survey of z>5.8 Quasars in the Sloan Digital Sky Survey I: Discovery of Three New Quasars and the Spatial Density of Luminous Quasars at z~6
• A Survey of z>5.7 Quasars in the Sloan Digital Sky Survey II: Discovery of Three Additional Quasars at z>6
• The 2dF QSO Redshift Survey - I. The Optical QSO Luminosity Function
• A Survey of z>5.7 Quasars in the Sloan Digital Sky Survey IV: Discovery of Seven Additional Quasars
• The role of black holes in galaxy formation and evolution
• A Survey of z>5.7 Quasars in the Sloan Digital Sky Survey III: Discovery of Five Additional Quasars
• The Multiwavelength Survey by Yale-Chile (MUSYC): Deep Medium-Band optical imaging and high quality 32-band photometric redshifts in the ECDF-S
• Simulation of Stellar Objects in SDSS Color Space
• Photometric Redshifts for the SDSS Early Data Release
• Constraining the Lifetime of Quasars from their Spatial Clustering
• Joint Cosmological Formation of QSOs and Bulge-dominated Galaxies
• The Space Density of High-Redshift QSOs in the GOODS Survey
• Quasar candidate selection and photometric redshift estimation based on SDSS and UKIDSS data
• Astroinformatics of galaxies and quasars: a new general method for photometric redshifts estimation
• Constraints from the Hubble Deep Field on High Redshift Quasar Models
• Infrared-Faint Radio Sources: A Cosmological View - AGN Number Counts, the Cosmic X-Ray Background and SMBH Formation

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• Photometric redshift estimation via deep learning
• Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy
• GalaxyNet: Connecting galaxies and dark matter haloes with deep neural networks and reinforcement learning in large volumes
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• A Comparison of Photometric Redshift Techniques for Large Radio Surveys
• Preliminary results of using k-Nearest Neighbours Regression to estimate the redshift of radio selected datasets
• Sacrificing information for the greater good: how to select photometric bands for optimal accuracy
• Estimating Spectroscopic Redshifts by Using k Nearest Neighbors Regression I. Description of Method and Analysis
• The Infrared Medium-deep Survey. III. Survey of Luminous Quasars at 4.7 $\le$ z $\le$ 5.4
• Deep redshift topological lensing: strategies for the T^3 candidate
• QSO redshift estimates from optical, near-infrared and ultraviolet colours