Probing Massive Black Hole Binary Populations with LISA
Probing Massive Black Hole Binary Populations with LISA
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DOI：
10.1093/mnras/stz3102
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发表时间：
2019-08
影响因子：
4.8
通讯作者：
Michael L. Katz;L. Kelley;F. Dosopoulou;Samantha J. H. Berry;L. Blecha;S. Larson
中科院分区：
文献类型：
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作者：
Michael L. Katz;L. Kelley;F. Dosopoulou;Samantha J. H. Berry;L. Blecha;S. Larson
ESA和NASA正在推进在2034年左右发射丽莎的计划。从插图宇宙学模拟的数据，我们提供了丽莎检测率的分析，伴随着合并的大质量黑洞人口的特征。总质量为105 - 1010 M <$的大质量黑洞是这项研究的重点。我们发展的大规模黑洞合并，形成在分离的模拟分辨率（10 kpc尺度）的顺序，通过合并与两种不同的治疗的二元大规模黑洞的演化过程。人口的合并时间，以及黑洞的物理性质，形成了每一个进化处理的统计基础。在此基础上，我们用蒙特卡罗方法合成了大量的大质量黑洞并合星族的实现，建立了模拟的丽莎探测星表。我们分析了我们的大质量黑洞二元演化模型如何影响检测率和相关的参数分布测量丽莎。利用我们的模型，我们发现对于质量大于105 M Ω的大质量黑洞，丽莎的大质量黑洞双星探测率为10.5 − 1 yr−1。这应该被视为一个下限，主要是因为我们的大质量黑洞样本不包括低于105 M质量的质量，这可能会显着增加观测到的速率。我们提出的原因，我们预测较低的检出率相比，许多文献。
ESA and NASA are moving forward with plans to launch LISA around 2034. With data from the Illustris cosmological simulation, we provide analysis of LISA detection rates accompanied by characterization of the merging massive black hole population. Massive black holes of total mass ∼105 − 1010M⊙ are the focus of this study. We evolve Illustris massive black hole mergers, which form at separations on the order of the simulation resolution (∼kpc scales), through coalescence with two different treatments for the binary massive black hole evolutionary process. The coalescence times of the population, as well as physical properties of the black holes, form a statistical basis for each evolutionary treatment. From these bases, we Monte Carlo synthesize many realizations of the merging massive black hole population to build mock LISA detection catalogs. We analyze how our massive black hole binary evolutionary models affect detection rates and the associated parameter distributions measured by LISA. With our models, we find massive black hole binary detection rates with LISA of ∼0.5 − 1 yr−1 for massive black holes with masses greater than 105M⊙. This should be treated as a lower limit primarily because our massive black hole sample does not include masses below 105M⊙, which may significantly add to the observed rate. We suggest reasons why we predict lower detection rates compared to much of the literature.