Distinguishing double neutron star from neutron star-black hole binary populations with gravitational wave observations
Distinguishing double neutron star from neutron star-black hole binary populations with gravitational wave observations
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DOI：
10.1103/physrevd.102.023025
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发表时间：
2020-05
影响因子：
5
通讯作者：
Margherita Fasano;Ka-wah Wong;A. Maselli;E. Berti;V. Ferrari;B. Sathyaprakash
中科院分区：
文献类型：
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作者：
Margherita Fasano;Ka-wah Wong;A. Maselli;E. Berti;V. Ferrari;B. Sathyaprakash
两颗中子星合并产生的引力波与质量相当的混合双星（其中一个伴星是黑洞）产生的引力波很难区分。低质量黑洞很有趣，因为它们可能是两颗中子星合并的结果，也可能是大质量恒星坍缩的结果，也可能是原始宇宙中物质密度过大的结果，也可能是中子星和暗物质相互作用的结果。引力波通过所谓的潮汐变形参数带有中子星内部组成的印记，该参数取决于恒星状态方程，对于黑洞等于零。我们提出了一种新的数据分析策略，由贝叶斯推理和机器学习驱动，利用引力波观测推断的潮汐变形性参数的分布来识别混合双星，即低质量黑洞。
Gravitational waves from the merger of two neutron stars cannot be easily distinguished from those produced by a comparable-mass mixed binary in which one of the companions is a black hole. Low-mass black holes are interesting because they could form in the aftermath of the coalescence of two neutron stars, from the collapse of massive stars, from matter overdensities in the primordial Universe, or as the outcome of the interaction between neutron stars and dark matter. Gravitational waves carry the imprint of the internal composition of neutron stars via the so-called tidal deformability parameter, which depends on the stellar equation of state and is equal to zero for black holes. We present a new data analysis strategy powered by Bayesian inference and machine learning to identify mixed binaries, hence low-mass black holes, using the distribution of the tidal deformability parameter inferred from gravitational-wave observations.