当前位置: X-MOL 学术Astrophys. J.  › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Multispectral Sirens: Gravitational-wave Cosmology with (Multi-) Subpopulations of Binary Black Holes
The Astrophysical Journal ( IF 4.8 ) Pub Date : 2024-11-20 , DOI: 10.3847/1538-4357/ad888b
Yin-Jie Li, 银杰 李, Shao-Peng Tang, 少鹏 唐, Yuan-Zhu Wang, 远瞩 王, Yi-Zhong Fan and 一中 范

The cosmic expansion rate can be directly measured with gravitational-wave (GW) data of the compact binary mergers by jointly constraining the mass function of the population and the cosmological model via the so-called spectral sirens. Such a method relies on the features in the mass functions, which may originate from some individual subpopulations and hence become blurred/indistinct due to the superposition of different subpopulations. In this work, we propose a novel approach to constrain the cosmic expansion rate with subpopulations of GW events, named multispectral sirens. The advantage of the multispectral sirens compared to the traditional spectral sirens is demonstrated by the simulation with the mock data. The application of this approach to the GWTC-3 data yields (median and symmetric 68.3% credible interval), which is about 19% tighter than the result inferred with the traditional spectral sirens utilizing a powerlaw+peak mass function. The incorporation of the bright standard siren GW170817 with a uniform prior in [10, 200] (log-uniform prior in [20,140]) Mpc−1 km s−1 gives (68.3% confidence level), corresponding to an improvement of ∼26% (23%) with respect to the measurement from sole GW170817.

中文翻译:


多光谱警报器:具有双黑洞的(多)亚群的引力波宇宙学



宇宙膨胀率可以通过紧凑的双星合并的引力波 (GW) 数据直接测量,方法是通过所谓的光谱警报器共同约束种群和宇宙学模型的质量函数。这种方法依赖于质量函数中的特征,这些特征可能来自一些单独的亚群,因此由于不同亚群的叠加而变得模糊/模糊。在这项工作中,我们提出了一种新方法,用 GW 事件的子群来限制宇宙膨胀率,称为多光谱警报器。与传统光谱警报器相比,多光谱警报器的优势通过模拟数据的模拟得到了证明。将这种方法应用于 GWTC-3 数据可产生(中位数和对称 68.3% 可信区间),这比使用幂律 + 峰值质量函数的传统光谱警报器推断的结果紧密约 19%。将明亮的标准警笛GW170817与 [10, 200]([20,140] 中的对数均匀先验)Mpc-1 km-s-1 中的均匀先验相结合,得到(68.3% 的置信度),对应于从鞋底GW170817测量的改进 ∼26% (23%)。
更新日期:2024-11-20
down
wechat
bug