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arXiv 1910.04565gr-qc
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揭开螺旋状双星黑洞的光谱

Unveiling the spectrum of inspiralling binary black holes

Soumen Roy, Anand S. Sengupta, K. G. Arun

摘要:

来自合并致密双星的引力波信号的高多极子在精确重建源性质方面起着至关重要的作用,带来了对基础物理和天体物理更深入和细致的理解。它们的影响在具有非对称质量的系统中最为明显,这些质量具有非正面的轨道几何形状。从任何单个孤立的合并事件中检测GW信号的更高多极是具有挑战性的,因为与占主导地位的四极模式相比,功率要小得多。在本文中,我们提出了一种新的方法,他们的检测相结合的多个事件的干涉引力波探测器。使用数据的时间-频率谱图来堆叠来自单独事件的信号中存在的次主导模式(的螺旋部分)。我们证明,这个过程增强了较高的多极组件的信噪比,从而导致其检测的机会增加。从蒙特卡罗模拟,我们估计,在两个探测器的符合中观察到的$\sim 100$事件的组合可以导致较高的多极分量的检测与$\geq$ 95\%的检测概率。先进的LIGO探测器预计将在一个月内以设计灵敏度记录这些双黑洞合并事件。我们还提出了使用我们的新方法从O 1和O2科学运行包含以前检测到的事件的数据分析结果。

英文摘要:

The higher-multipoles of gravitational wave signals from coalescing compact binaries play a vital role in the accurate reconstruction of source properties, bringing about a deeper and nuanced understanding of fundamental physics and astrophysics. Their effect is most pronounced in systems with asymmetric masses having an orbital geometry that is not face-on. The detection of higher-multipoles of GW signals from any single, isolated merger event is challenging, as there is much less power in comparison to the dominant quadrupole mode. In this paper, we present a new method for their detection by combining multiple events observed in interferometric gravitational wave detectors. Sub-dominant modes present in (the inspiral part of) the signal from separate events are stacked using time-frequency spectrogram of the data. We demonstrate that this procedure enhances the signal-to-noise ratio of the higher-multipole components and thereby leads to increased chances of their detection. From Monte-Carlo simulations, we estimate that a combination of $\sim 100$ events observed in two-detector coincidence can lead to the detection of the higher-multipole components with a $\geq$ 95\% detection probability. The advanced-LIGO detectors are expected to record these many binary black hole merger events within a month of operation at design sensitivity. We also present results from the analysis of data from O1 and O2 science runs containing previously detected events using our new method.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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