Discriminating between different scenarios for the formation and evolution of massive black holes with LISA,Physical Review D

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Discriminating between different scenarios for the formation and evolution of massive black holes with LISA
Physical Review D ( IF 4.6 ) Pub Date : 2021-10-21 , DOI: 10.1103/physrevd.104.083027
Alexandre Toubiana _{1,

2} , Kaze W. K. Wong ₃ , Stanislav Babak _{1,

4} , Enrico Barausse _{5,

6} , Emanuele Berti ₃ , Jonathan R. Gair _{7,

8} , Sylvain Marsat ₁ , Stephen R. Taylor ₉

Affiliation

Electromagnetic observations have provided strong evidence for the existence of massive black holes in the center of galaxies, but their origin is still poorly known. Different scenarios for the formation and evolution of massive black holes lead to different predictions for their properties and merger rates. LISA observations of coalescing massive black hole binaries could be used to reverse engineer the problem and shed light on these mechanisms. In this paper, we introduce a pipeline based on hierarchical Bayesian inference to infer the mixing fraction between different theoretical models by comparing them to LISA observations of massive black hole mergers. By testing this pipeline against simulated LISA data, we show that it allows us to accurately infer the properties of the massive black hole population as long as our theoretical models provide a reliable description of the Universe. We also show that measurement errors, including both instrumental noise and weak lensing errors, have little impact on the inference.

中文翻译：

用LISA区分大质量黑洞形成和演化的不同场景

电磁观测为星系中心存在大质量黑洞提供了强有力的证据，但它们的起源仍知之甚少。大质量黑洞形成和演化的不同情景导致对其性质和合并率的不同预测。LISA 对合并大质量黑洞双星的观测可用于对问题进行逆向工程并阐明这些机制。在本文中，我们引入了一种基于分层贝叶斯推理的管道，通过将它们与 LISA 对大规模黑洞合并的观测进行比较来推断不同理论模型之间的混合分数。通过针对模拟 LISA 数据测试此管道，我们表明，只要我们的理论模型提供了对宇宙的可靠描述，它就可以让我们准确地推断出大质量黑洞群的特性。我们还表明，测量误差，包括仪器噪声和弱透镜误差，对推理的影响很小。

更新日期：2021-10-22

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