论文标题
一个统治它们的渠道?使用多个构造途径来限制二进制黑洞的起源
One Channel to Rule Them All? Constraining the Origins of Binary Black Holes using Multiple Formation Pathways
论文作者
论文摘要
重力波瞬变的第二个LIGO-VIRGO目录已经使二进制黑洞的观测样品倍增了三倍。我们使用五个最先进的二进制黑洞种群模型组成的套件分析了该目录,涵盖了一系列孤立和动态的形成通道,并推断出通道之间的分支部分以及对影响合并观察性特性的不确定物理过程的限制。鉴于我们的一组地层模型,我们发现基础和可检测人群的分支分数之间存在显着差异,并且检测的多样性表明多个地层通道正在发挥作用。与检测到的人群主导的任何单个通道相比,通道的混合物非常优选:单个通道不会造成二进制黑洞的观测样本的$ \ simeq 70 \%$。我们计算模型中出生旋转假设和常见的包络效率之间的偏好,有利于$ \ lyssim 0.1 $的孤立黑洞的出生旋转,以及略微偏爱$ \ gtrsim 2.0 $的共同包膜效率,同时强烈不利于高效率低效率的普通型造成良好的常见造成者。我们表明,在解释引力波目录时要考虑多个通道至关重要,因为当不考虑不考虑贡献形成场景或假定不正确的物理处方时,对分支分数和物理处方的推论变得有偏见。尽管我们的定量结果可能会受到模型预测中不确定的假设的影响,但我们的方法论能够包括具有更新的理论考虑和其他编队渠道的模型。
The second LIGO-Virgo catalog of gravitational wave transients has more than quadrupled the observational sample of binary black holes. We analyze this catalog using a suite of five state-of-the-art binary black hole population models covering a range of isolated and dynamical formation channels and infer branching fractions between channels as well as constraints on uncertain physical processes that impact the observational properties of mergers. Given our set of formation models, we find significant differences between the branching fractions of the underlying and detectable populations, and that the diversity of detections suggests that multiple formation channels are at play. A mixture of channels is strongly preferred over any single channel dominating the detected population: an individual channel does not contribute to more than $\simeq 70\%$ of the observational sample of binary black holes. We calculate the preference between the natal spin assumptions and common envelope efficiencies in our models, favoring natal spins of isolated black holes of $\lesssim 0.1$, and marginally preferring common envelope efficiencies of $\gtrsim 2.0$ while strongly disfavoring highly inefficient common envelopes. We show that it is essential to consider multiple channels when interpreting gravitational wave catalogs, as inference on branching fractions and physical prescriptions becomes biased when contributing formation scenarios are not considered or incorrect physical prescriptions are assumed. Although our quantitative results can be affected by uncertain assumptions in model predictions, our methodology is capable of including models with updated theoretical considerations and additional formation channels.