5 October 2012 Survey of approaches for targeting quasars
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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.
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Yanxia Zhang, Yanxia Zhang, Yong-Heng Zhao, Yong-Heng Zhao, } "Survey of approaches for targeting quasars", Proc. SPIE 8451, Software and Cyberinfrastructure for Astronomy II, 845135 (5 October 2012); doi: 10.1117/12.925298; https://doi.org/10.1117/12.925298
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