论文标题
Pearson交叉相关在前四个黑洞二进制合并中
Pearson cross-correlation in the first four black hole binary mergers
论文作者
论文摘要
我们采用Pearson互相关度量来分析Ligo Hanford和Ligo Livingston探测器数据流，周围是GW150914，GW151012，GW151226和GW170104。我们发现，Pearson互相关方法对这些信号敏感，当Ligo Scientific和Pirgo协作重建的黑洞二进制文件正在合并时，相关性达到了峰值。我们将所获得的互相关与模拟的高斯噪声数据和Ligo数据中产生的统计相关性波动进行比较，该波动在没有任何事件的情况下。我们对观察到的互相关的重要性的结果与基于匹配的过滤器分析的Ligo Scientific和处女座协作宣布的结果广泛一致。在相同的数据中，如果我们减去与已宣布的信号相对应的最大似然波形式，则没有剩余的互相相关持续在统计学上显着的水平。
We adopt the Pearson cross-correlation measure to analyze the LIGO Hanford and LIGO Livingston detector data streams around the events GW150914, GW151012,GW151226 and GW170104. We find that the Pearson cross-correlation method is sensitive to these signals, with correlations peaking when the black hole binaries reconstructed by the LIGO Scientific and Virgo Collaborations, are merging. We compare the obtained cross-correlations with the statistical correlation fluctuations arising in simulated Gaussian noise data and in LIGO data at times when no event is claimed. Our results for the significance of the observed cross-correlations are broadly consistent with those announced by the LIGO Scientific and Virgo Collaborations based on matched-filter analysis. In the same data, if we subtract the maximum likelihood waveforms corresponding to the announced signals, no residual cross-correlations persists at a statistically significant level.
