Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers
Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers
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DOI：
10.1103/physrevd.106.084033
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发表时间：
2021-10
影响因子：
5
通讯作者：
C. Hanna;P. Joshi;R. Huxford;K. Cannon;S. Caudill;C. Chan;B. Cousins;J. Creighton;B. Ewing;Miguel Fernandez;H. Fong;P. Godwin;R. Magee;D. Meacher;C. Messick;S. Morisaki;D. Mukherjee;H. Ohta;A. Pace;S. Privitera;S. Sachdev;S. Sakon;Divya Singh;R. Tapia;L. Tsukada;D. Tsuna;T. Tsutsui;K. Ueno;A. Viets;L. Wade;M. Wade;Jonathan Wang
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文献类型：
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作者：
C. Hanna;P. Joshi;R. Huxford;K. Cannon;S. Caudill;C. Chan;B. Cousins;J. Creighton;B. Ewing;Miguel Fernandez;H. Fong;P. Godwin;R. Magee;D. Meacher;C. Messick;S. Morisaki;D. Mukherjee;H. Ohta;A. Pace;S. Privitera;S. Sachdev;S. Sakon;Divya Singh;R. Tapia;L. Tsukada;D. Tsuna;T. Tsutsui;K. Ueno;A. Viets;L. Wade;M. Wade;Jonathan Wang
我们提出了一种新型的重力波检测算法，该算法在紧凑的二进制参数空间上随机进行匹配的滤波器搜索，而不是依靠固定的模板波形。该技术在计算成本和敏感性方面具有标准模板驱动的管道竞争。但是，分析的复杂性更为简单，可以简单地在计算机的异质网格上简化配置和水平缩放。为了证明该方法，我们分析了2017年7月27日00:00 UTC的大约一个月的公共LIGO数据 - 2017年8月25日22:00 UTC，并恢复了八个已知的自信引力候选者。我们还注入模拟的二进制黑洞（BBH）信号以证明灵敏度。
We present a novel gravitational wave detection algorithm that conducts a matched filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is competitive with standard template-bank-driven pipelines in both computational cost and sensitivity. However, the complexity of the analysis is simpler allowing for easy configuration and horizontal scaling across heterogeneous grids of computers. To demonstrate the method we analyze approximately one month of public LIGO data from July 27 00:00 2017 UTC - Aug 25 22:00 2017 UTC and recover eight known confident gravitational wave candidates. We also inject simulated binary black hole (BBH) signals to demonstrate the sensitivity.