4.7 Article

SUB-PARSEC SUPERMASSIVE BINARY QUASARS: EXPECTATIONS AT z < 1

期刊

ASTROPHYSICAL JOURNAL LETTERS
卷 703, 期 1, 页码 L86-L89

出版社

IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/703/1/L86

关键词

black hole physics; cosmology: theory; galaxies: nuclei; quasars: general

向作者/读者索取更多资源

We investigate the theoretical expectations for detections of supermassive binary black holes that can be identified as sub-parsec luminous quasars. To date, only two candidates have been selected in a sample comprising 17,500 sources selected from the Sloan Digital Sky Survey (SDSS) Quasar Catalog at z < 0.70. In this Letter, we use models of assembly and growth of supermassive black holes (SMBHs) in hierarchical cosmologies to study the statistics and observability of binary quasars at sub-parsec separations. Our goal is twofold: (1) to test if such a scarce number of binaries is consistent with theoretical prediction of SMBH merger rates and (2) to provide additional predictions at higher redshifts and at lower flux levels. We determine the cumulative number of expected binaries in a complete volume-limited sample. Motivated by Boroson & Lauer, we apply the SDSS quasar luminosity cut (M-i < -22) to our theoretical sample, deriving an upper limit to the observable binary fraction. We find that sub-parsec quasar binaries are intrinsically rare. Our best models predict similar to 0.01 deg(-2) sub-parsec binary quasars with separations below similar to 10(4) Schwarzschild radii (upsilon(orb) > 2000 kms) at z < 0.7, which represent a fraction similar to 6 x 10(-4) of unabsorbed quasars in our theoretical sample. In a complete sample of similar to 10,000 sources, we therefore predict an upper limit of similar to 10 sub-parsec binary quasars. The number of binaries increases rapidly with increasing redshift. The decreasing lifetime with SMBH binary mass suggests that lowering the luminosity threshold does not lead to a significant increase in the number of detectable sub-parsec binary quasars.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据