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Exploring the Quasar Luminosity Function with Quasars Selected by both Color and Variability.

机译：利用按颜色和可变性选择的类星体研究类星体的光度函数。

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摘要

A non-parametric Bayesian classification selection algorithm was used to demonstrate that a combination of optical colors and variability features improves quasar classification efficiency and completeness over the use of colors alone, suggesting that this is a good set of features to use in classification algorithms for future time-domain focused sky surveys. These features were used to identify 35,820 type 1 quasar candidates in a 239 square deg field of the Sloan Digital Sky Survey (SDSS) Stripe 82. Color analysis was performed on 5-band single- and multi-epoch SDSS optical photometry and variability parameters were calculated by fitting the structure function of each object in each band with a power law model. Using variability alone, colors alone, and combining variability and colors, quasar completeness of 91%, 93%, and 97% and efficiency of 98%, 98%, and 97%, respectively, was achieved. Particular improvement was seen in the selection of quasars at 2.7 < z < 3.5 where quasars and stars have similar optical colors. Of the 22,867 quasar candidates that are not spectroscopically confirmed, 95.7% are dimmer than coadded i-band magnitude of 19.9, the cut off for spectroscopic follow-up on Stripe 82. Brighter than 19.9, 5.7% more quasar candidates were found without confirming spectra in sky regions otherwise considered complete. In addition to calculating empirical optical photometric redshifts for all candidate quasars, astrometric redshifts were calculated using parameters determined by measuring the differential chromatic refraction (DCR) effect with the purpose of breaking degeneracies in the photometric redshifts. The combined astro-photometric redshifts are more accurate than optical and near-infrared photometric redshifts. Potential observation schedules for the Large Synoptic Survey Telescope (LSST) were analyzed to determine how well quasars of different redshifts can be distinguished using the DCR effect. The resulting quasar sample has sufficient purity (and statistically correctable incompleteness) to produce a luminosity function comparable to those determined by spectroscopic investigations with photometric selection and redshift estimation. The quasar luminosity function of a uniformly-selected spectroscopic quasar sample, grouped according to emission-line properties, suggests that the space density of quasars with different underlying spectral energy distributions (SEDs) has evolved differently with redshift, peaking at different times.
机译：使用非参数贝叶斯分类选择算法来证明光学颜色和可变性特征的组合比单独使用颜色可提高类星体的分类效率和完整性，表明这是将来在分类算法中可以使用的一组很好的特征时域重点天空调查。这些功能用于在Sloan数字天空测量（SDSS）条带82的239平方英寸视野中识别35,820个1类类星体候选对象。对5波段单周期和多周期SDSS光学光度法进行了颜色分析，并且可变性参数为通过用幂律模型拟合每个频带中每个对象的结构函数来计算。单独使用可变性，单独使用颜色，并结合可变性和颜色，可实现类星体完整性分别为91％，93％和97％，效率为98％，98％和97％。在2.7

著录项

  • 作者

    Peters, Christina M.;

  • 作者单位

    Drexel University.;

  • 授予单位 Drexel University.;
  • 学科 Astrophysics.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 128 p.
  • 总页数 128
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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