论文标题

宇宙学和天体物理种群模型的不确定性和偏见来自统计黑暗警报器

Uncertainty and bias of cosmology and astrophysical population model from statistical dark sirens

论文作者

Yu, Hang, Seymour, Brian, Wang, Yijun, Chen, Yanbei

论文摘要

从合并紧凑型二进制的重力波(GW)辐射是标准警报器,因为每个事件的光度距离可以直接从信号的振幅中测量。使用GW警笛限制宇宙学的一种可能性是对二进制黑洞(BBH)事件的人群进行统计推断。从本质上讲,这种统计方法可以看如下。我们可以通过更改宇宙学参数来修改观察到的BBH事件的分布形状,直到最终与天体物理种群模型构建的分布匹配,从而使我们能够确定宇宙学参数。在这项工作中,我们通过研究事件分布中包含的渔民信息,从这种统计暗警笛中得出了宇宙学参数的Cramér-rao绑定。我们的研究提供了分析见解,并可以快速而准确地估计暗警笛宇宙学的统计准确性。此外,由于合并速率和质量分布的未建模子结构,我们考虑了宇宙学的偏见。我们发现天体物理模型中的$ 1 \%$偏差可能会导致超过1美元的$ $ $错误在哈勃常数中。当检测到$ 10^4 $ BBH事件时,这可能会限制黑暗警笛宇宙学的准确性。

Gravitational-wave (GW) radiation from a coalescing compact binary is a standard siren as the luminosity distance of each event can be directly measured from the amplitude of the signal. One possibility to constrain cosmology using the GW siren is to perform statistical inference on a population of binary black hole (BBH) events. In essence, this statistical method can be viewed as follows. We can modify the shape of the distribution of observed BBH events by changing cosmological parameters until it eventually matches the distribution constructed from an astrophysical population model, thereby allowing us to determine the cosmological parameters. In this work, we derive the Cramér-Rao bound for both cosmological parameters and those governing the astrophysical population model from this statistical dark siren method by examining the Fisher information contained in the event distribution. Our study provides analytical insights and enables fast yet accurate estimations of the statistical accuracy of dark siren cosmology. Furthermore, we consider the bias in cosmology due to unmodeled substructures in the merger rate and the mass distribution. We find a $1\%$ deviation in the astrophysical model can lead to a more than $1\%$ error in the Hubble constant. This could limit the accuracy of dark siren cosmology when there are more than $10^4$ BBH events detected.

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