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Proceedings Paper

Survey of approaches for targeting quasars
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Paper Abstract

The study of quasars is of great importance to the formation and evolution of galaxies and the early history of the universe, especially high redshift quasars. With the development and employment of large sky spectroscopic survey projects (e.g. 2dF, SDSS), the number of quasars increases to more than 200,000. For improving the efficiency of high-cost telescopes, careful selecting observational targets is necessary. Therefore various targeting quasar algorithms are used and developed based on different data. We review them in detail. Some statistical approaches are based on photometric color, variability, UV-excess, BRX, radio properties, color-color cut and so on. Automated methods include support vector machines (SVMs), kernel density estimation (KDE), artificial neural networks (ANNs), extreme-deconvolution method, probabilistic principal surfaces (PPS) and the negative entropy clustering (NEC), etc. In addition, we touch upon some quasar candidate catalogues created by different algorithms.

Paper Details

Date Published: 5 October 2012
PDF: 13 pages
Proc. SPIE 8451, Software and Cyberinfrastructure for Astronomy II, 845135 (5 October 2012); doi: 10.1117/12.925298
Show Author Affiliations
Yanxia Zhang, Key Lab. of Astronomical Optics & Technology, Nanjing Institute of Astronomical Optics & Technology (China)
National Astronomical Observatories, Nanjing Institute of Astronomal Optics & Technology (China)
Yong-Heng Zhao, Key Lab. of Astronomical Optics & Technology, Nanjing Institute of Astronomical Optics & Technology (China)
National Astronomical Observatories, Nanjing Institute of Astronomal Optics & Technology (China)


Published in SPIE Proceedings Vol. 8451:
Software and Cyberinfrastructure for Astronomy II
Nicole M. Radziwill; Gianluca Chiozzi, Editor(s)

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