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arXiv 1809.02138astro-ph.HE
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作为周期变量AGN的大量BH二进制

Massive BH Binaries as Periodically-Variable AGN

Luke Zoltan Kelley, Zoltán Haiman, Alberto Sesana, Lars Hernquist

摘要:

大质量黑洞(MBH)双星,预计将形成合并后,他们的母星系,产生引力波,这将是可检测的脉冲星定时阵列在纳赫兹频率(年周期)。虽然在电磁观测中还没有确认的紧凑的MBH双星系统,但最近在AGN可变性的光学调查中已经确定了大量的候选者。使用宇宙学,流体动力学模拟相结合,全面,半解析二进制合并模型,分析活动星系核光谱和变异处方,我们计算预期的电磁探测率MBH二进制周期性变量活动星系核。特别是,我们考虑两个独立的变异模型:(i)多普勒助推由于大的轨道速度,和(ii)流体动力学的变化,其中燃料的MBH吸积盘定期调制的同伴。我们的模型预测,许多MBH二进制文件应该存在,并在现有的数据中区分。特别是,我们的基准模型产生的期望值$0.2$(多普勒)和$5$(流体动力学)二进制可识别的CRTS,而$20$和$100$预计经过五年的LSST观测。在大多数系统中,亮度变化太小而无法分辨,但活动星系核中几乎所有红移为$z \lesssim 0.6$的$1\%$都可能存在于大质量双星中。我们分析了可观测系统的预测二进制参数及其选择偏差,并包括我们的模型参数和不确定性的广泛讨论。

英文摘要:

Massive black-hole (MBH) binaries, which are expected to form following the merger of their parent galaxies, produce gravitational waves which will be detectable by Pulsar Timing Arrays at nanohertz frequencies (year periods). While no confirmed, compact MBH binary systems have been seen in electromagnetic observations, a large number of candidates have recently been identified in optical surveys of AGN variability. Using a combination of cosmological, hydrodynamic simulations; comprehensive, semi-analytic binary merger models; and analytic AGN spectra and variability prescriptions; we calculate the expected electromagnetic detection rates of MBH binaries as periodically variable AGN. In particular, we consider two independent variability models: (i) Doppler boosting due to large orbital velocities, and (ii) hydrodynamic variability in which the fueling of MBH accretion disks is periodically modulated by the companion. Our models predict that numerous MBH binaries should be present and distinguishable in the existing data. In particular, our fiducial models produce an expectation value of $0.2$ (Doppler) and $5$ (hydrodynamic) binaries to be identifiable in CRTS, while $20$ and $100$ are expected after five years of LSST observations. The brightness variations in most systems are too small to be distinguishable, but almost $1\%$ of AGN at redshifts $z \lesssim 0.6$ could be in massive binaries. We analyze the predicted binary parameters of observable systems and their selection biases, and include an extensive discussion of our model parameters and uncertainties.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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