You Can’t Always Get What You Want: The Impact of Prior Assumptions on Interpreting GW190412

You Can’t Always Get What You Want: The Impact of Prior Assumptions on Interpreting GW190412
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DOI:
10.3847/2041-8213/aba8ef
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发表时间:
2020-06
期刊:
The Astrophysical Journal Letters
影响因子:
--
通讯作者:
M. Zevin;C. Berry;S. Coughlin;K. Chatziioannou;S. Vitale
M. Zevin;C. Berry;S. Coughlin;K. Chatziioannou;S. Vitale
中科院分区:
其他
文献类型:
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作者:
M. Zevin;C. Berry;S. Coughlin;K. Chatziioannou;S. Vitale

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GW 190412是第一个观测到质量不等的黑洞双星。GW 190412的质量不对称性,沿着测量到的正有效内旋自旋,使得可以推断出一个组成黑洞的自旋:系统中的主黑洞被发现有一个无量纲的自旋幅度在和之间(90%可信范围)。我们调查如何选择先验的自旋幅度和倾斜的组件黑洞的影响GW 190412的参数估计的鲁棒性,并报告贝叶斯因子在一套先验假设。根据用于描述信号的波形族,我们发现与只允许次级黑洞旋转的情况相比,初级黑洞旋转的支持要么是边缘到中等(:1-:1),要么是强(:1)。我们展示了这些选择如何影响参数估计,并发现GW 190412的非对称质量和正有效内旋自旋是定性的,但不是定量的,对先前的假设是鲁棒的。我们的研究结果强调了在解释观测结果时考虑天体物理学动机或基于人口的先验以及考虑其数据的相对支持的重要性。
GW190412 is the first observation of a black hole binary with definitively unequal masses. GW190412's mass asymmetry, along with the measured positive effective inspiral spin, allowed for inference of a component black hole spin: the primary black hole in the system was found to have a dimensionless spin magnitude between and (90% credible range). We investigate how the choice of priors for the spin magnitudes and tilts of the component black holes affect the robustness of parameter estimates for GW190412, and report Bayes factors across a suite of prior assumptions. Depending on the waveform family used to describe the signal, we find either marginal to moderate ( :1– :1) or strong (≳ :1) support for the primary black hole being spinning compared to cases where only the secondary is allowed to have spin. We show how these choices influence parameter estimates, and find the asymmetric masses and positive effective inspiral spin of GW190412 to be qualitatively, but not quantitatively, robust to prior assumptions. Our results highlight the importance of both considering astrophysically motivated or population-based priors in interpreting observations and considering their relative support from the data.