论文标题
涵盖您的基础：二进制黑洞人口的全面数据驱动表征
Cover Your Basis: Comprehensive Data-Driven Characterization of the Binary Black Hole Population
论文作者
论文摘要
我们介绍了第一个完整的非参数模型，用于二进制黑洞（BBH）种群的天体物理分布。我们使用这些模型构建的，对迄今为止对BBH人群进行最全面的数据驱动研究，同时拟合了BBH质量比，旋转幅度和错误对准的非参数模型，以及红移分布。使用GWTC-3，我们报告了先前使用类似灵活的质量分布模型恢复的相同功能，最值得注意的是，合并率的峰值在$ {\ sim} 10 \，m_ \ odot $和$ {\ sim} 35 \，m_ \ odot $中。我们的模型报告说，在低初级质量下抑制了合并率，质量比分布与功率定律一致。我们推断出一级旋转错位的分布，该分布远离对准的峰值，这支持了最近工作的结论。我们发现与先前的自旋幅度分布的推断相当一致：大多数BBH旋转很小（$ a <0.5 $），分配峰值为$ a \ sim0.2 $，并且对非旋转亚群有温和的支持，可以用较大的目录解决。通过调制功率法，描述了BBH合并率在红移中的演变，我们看到速率演变在$ z \ sim0.2-0.5 $下变平或减少的提示，但完整的分布完全与单调增长的幂律完全一致。最后，我们讨论了我们的新发现的天体物理背景以及引力波种群推断中的非参数方法如何在我们进入引力波天文学的数据丰富的时代时，可以与参数方法相互补充。
We introduce the first complete non-parametric model for the astrophysical distribution of the binary black hole (BBH) population. Constructed from basis splines, we use these models to conduct the most comprehensive data-driven investigation of the BBH population to date, simultaneously fitting non-parametric models for the BBH mass ratio, spin magnitude and misalignment, and redshift distributions. With GWTC-3, we report the same features previously recovered with similarly flexible models of the mass distribution, most notably the peaks in merger rates at primary masses of ${\sim}10\,M_\odot$ and ${\sim}35\,M_\odot$. Our model reports a suppressed merger rate at low primary masses and a mass ratio distribution consistent with a power law. We infer a distribution for primary spin misalignments that peaks away from alignment, supporting conclusions of recent work. We find broad agreement with the previous inferences of the spin magnitude distribution: the majority of BBH spins are small ($a<0.5$), the distribution peaks at $a\sim0.2$, and there is mild support for a non-spinning subpopulation, which may be resolved with larger catalogs. With a modulated power law describing the BBH merger rate's evolution in redshift, we see hints of the rate evolution either flattening or decreasing at $z\sim0.2-0.5$, but the full distribution remains entirely consistent with a monotonically increasing power law. We conclude with a discussion of the astrophysical context of our new findings and how non-parametric methods in gravitational-wave population inference are uniquely poised to complement to the parametric approach as we enter the data-rich era of gravitational-wave astronomy.
