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arXiv 2008.13704astro-ph.COgr-qc
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LIGO-Virgo合并的贝叶斯分析：原始与天体物理学黑洞种群

Bayesian analysis of LIGO-Virgo mergers: Primordial vs. astrophysical black hole populations

Alex Hall, Andrew D. Gow, Christian T. Byrnes

备注：
29+8 pages, 18 figures. Minor edits to match version published in Physical Review D
发表信息：
Phys. Rev. D 102, 123524 (2020)
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摘要：

我们进行了彻底的贝叶斯分析的可能性，在引力波中看到的黑洞合并事件是原始的黑洞（PBH）合并。使用最新的合并率模型PBH二进制从对数正态质量函数，我们计算后验参数约束和贝叶斯证据使用的前两个观测运行的LIGO-Virgo的数据。我们占理论上的不确定性，由于周围的PBH，这可能会抑制合并率显着的二进制中断。我们还考虑了简单的天体物理学动机的模型，并发现这些是赞成决定性的PBH的情况下，量化的贝叶斯证据比。仔细注意参数先验和模型拟合质量的影响，我们表明，证据比可以通过比较预测的啁啾质量分布的数据来理解。我们确定了啁啾质量的后验预测分布作为区分模型的重要工具。与天体物理模型相比，所有合并都是PBH双星的模型是非常不利的，部分原因是过度预测了具有$\mathcal{M}_{\rm chirp} \gtrsim 40 \, M_\odot$的重系统，并且在观测质量范围内正偏度与观测结果不匹配。我们发现，通过增加一个最大的质量截止，双峰质量函数，或施加PBH二进制形式在晚些时候，拟合没有显着改善。我们认为，一个成功的PBH模型必须要么修改对数正态形状的初始质量函数显着或放弃的假设，所有观察到的合并双星是原始的。我们开发和应用技术分析PBH模型与引力波数据，这将是必要的强大的统计推断的引力波源样本大小的增加。

英文摘要：

We conduct a thorough Bayesian analysis of the possibility that the black hole merger events seen in gravitational waves are primordial black hole (PBH) mergers. Using the latest merger rate models for PBH binaries drawn from a lognormal mass function we compute posterior parameter constraints and Bayesian evidences using data from the first two observing runs of LIGO-Virgo. We account for theoretical uncertainty due to possible disruption of the binary by surrounding PBHs, which can suppress the merger rate significantly. We also consider simple astrophysically motivated models and find that these are favoured decisively over the PBH scenario, quantified by the Bayesian evidence ratio. Paying careful attention to the influence of the parameter priors and the quality of the model fits, we show that the evidence ratios can be understood by comparing the predicted chirp mass distribution to that of the data. We identify the posterior predictive distribution of chirp mass as a vital tool for discriminating between models. A model in which all mergers are PBH binaries is strongly disfavoured compared with astrophysical models, in part due to the over-prediction of heavy systems having $\mathcal{M}_{\rm chirp} \gtrsim 40 \, M_\odot$ and positive skewness over the range of observed masses which does not match the observations. We find that the fit is not significantly improved by adding a maximum mass cut-off, a bimodal mass function, or imposing that PBH binaries form at late times. We argue that a successful PBH model must either modify the lognormal shape of the initial mass function significantly or abandon the hypothesis that all observed merging binaries are primordial. We develop and apply techniques for analysing PBH models with gravitational wave data which will be necessary for robust statistical inference as the gravitational wave source sample size increases.

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