Effects of data quality vetoes on a search for compact binary coalescences in Advanced LIGO's first observing run
Effects of data quality vetoes on a search for compact binary coalescences in Advanced LIGO's first observing run
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DOI：
10.1088/1361-6382/aaaafa
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发表时间：
2018-03-22
影响因子：
3.5
通讯作者：
Zweizig, J.
中科院分区：
文献类型：
--
作者：
Abbott, B. P.;Abbott, R.;Zweizig, J.
Advanced LIGO的第一次观测从2015年9月12日持续了4个月，在此期间，直接从两个双黑洞系统（即GW 150914和GW 151226）中检测到引力波。对引力波的可靠探测需要对仪器瞬变和伪影的理解，这会降低搜索的灵敏度。对探测器数据质量的研究可以深入了解仪器伪影的原因，并产生特定于搜索的数据质量否决，以减轻有问题数据的影响。在本文中，从分析时间的噪声数据的系统去除，以提高紧凑的二元聚结搜索的灵敏度。PyCBC管道的输出是一个基于Python的代码包，用于从紧凑的二元聚结中搜索引力波信号，它被用作改进的指标。GW150914是一个足够大的信号，去除噪声数据并不能提高其显著性。然而，删除数据与多余的噪音减少了两个数量级以上的虚假警报率的GW 151226，从1在770年到小于1在186000年。
The first observing run of Advanced LIGO spanned 4 months, from 12 September 2015 to 19 January 2016, during which gravitational waves were directly detected from two binary black hole systems, namely GW150914 and GW151226. Confident detection of gravitational waves requires an understanding of instrumental transients and artifacts that can reduce the sensitivity of a search. Studies of the quality of the detector data yield insights into the cause of instrumental artifacts and data quality vetoes specific to a search are produced to mitigate the effects of problematic data. In this paper, the systematic removal of noisy data from analysis time is shown to improve the sensitivity of searches for compact binary coalescences. The output of the PyCBC pipeline, which is a python-based code package used to search for gravitational wave signals from compact binary coalescences, is used as a metric for improvement. GW150914 was a loud enough signal that removing noisy data did not improve its significance. However, the removal of data with excess noise decreased the false alarm rate of GW151226 by more than two orders of magnitude, from 1 in 770 yr to less than 1 in 186 000 yr.