Fast Parameter Estimation of Binary Mergers for Multimessenger Follow-up
Fast Parameter Estimation of Binary Mergers for Multimessenger Follow-up
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DOI：
10.3847/2041-8213/abca9e
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
D. Finstad;Duncan A. Brown
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文献类型：
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作者：
D. Finstad;Duncan A. Brown
大量的人力和观测资源一直致力于对Advanced LIGO和Virgo探测到的引力波事件进行电磁跟踪。随着LIGO和Virgo的灵敏度提高，探测到的源的比率将增加。Margalit和Metzger（2019）建议可能有必要优先考虑对未来事件的观察。最佳优先级需要快速测量引力波事件的质量和自旋，因为这些可以确定任何电磁辐射的性质。我们将康沃尔语（2013）和Zackay等人（2018）的相对分箱方法扩展到相干检测器网络统计。我们表明，该方法可以从匹配过滤器搜索的输出中播种，并在贝叶斯参数测量框架中使用，以在32个CPU内核上检测20分钟内产生源参数的边缘化后验概率密度。我们证明，该算法产生无偏估计的参数与运行参数估计使用标准的引力波的可能性相同的精度。我们鼓励在未来的LIGO-Virgo观测运行中采用这种方法，以便快速传播所探测事件的参数，从而使观测界能够充分利用其资源。
Significant human and observational resources have been dedicated to electromagnetic follow-up of gravitational-wave events detected by Advanced LIGO and Virgo. As the sensitivity of LIGO and Virgo improves, the rate of sources detected will increase. Margalit & Metzger (2019) have suggested that it may be necessary to prioritize observations of future events. Optimal prioritization requires a rapid measurement of a gravitational-wave event’s masses and spins, as these can determine the nature of any electromagnetic emission. We extend the relative binning method of Cornish (2013) and Zackay et al. (2018) to a coherent detector-network statistic. We show that the method can be seeded from the output of a matched-filter search and used in a Bayesian parameter measurement framework to produce marginalized posterior probability densities for the source’s parameters within 20 minutes of detection on 32 CPU cores. We demonstrate that this algorithm produces unbiased estimates of the parameters with the same accuracy as running parameter estimation using the standard gravitational-wave likelihood. We encourage the adoption of this method in future LIGO–Virgo observing runs to allow fast dissemination of the parameters of detected events so that the observing community can make best use of its resources.