Inference with finite time series: Observing the gravitational Universe through windows
Inference with finite time series: Observing the gravitational Universe through windows
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DOI：
10.1103/physrevresearch.3.043049
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发表时间：
2021-06
影响因子：
4.2
通讯作者：
C. Talbot;E. Thrane;S. Biscoveanu;Rory J. E. Smith
中科院分区：
文献类型：
--
作者：
C. Talbot;E. Thrane;S. Biscoveanu;Rory J. E. Smith
时间序列分析在包括引力波天文学在内的许多科学领域中无处不在，其中分析应变时间序列以推断引力波源的性质，例如，黑洞和中子星在引力波瞬变研究中，通常采用锥形窗函数来减少数据段锐边的光谱伪影的影响。我们表明，传统的锥形数据分析未能考虑到频率箱之间的协方差，这是所有有限的时间序列-无论选择的窗口函数。我们讨论了这种协方差的起源，并表明，随着引力波探测数量的增长，以及我们获得更多的高信噪比事件，这种协方差将成为一个不可忽略的系统误差源。我们推导出一个框架，模型的相关性引起的窗口函数，并证明了这种解决方案使用的数据从第一个LIGO-处女座瞬态目录和模拟高斯噪声。
Time series analysis is ubiquitous in many fields of science including gravitational-wave astronomy, where strain time series are analyzed to infer the nature of gravitational-wave sources, e.g., black holes and neutron stars. It is common in gravitational-wave transient studies to apply a tapered window function to reduce the effects of spectral artifacts from the sharp edges of data segments. We show that the conventional analysis of tapered data fails to take into account covariance between frequency bins, which arises for all finite time series -- no matter the choice of window function. We discuss the origin of this covariance and show that as the number of gravitational-wave detections grows, and as we gain access to more high signal-to-noise ratio events, this covariance will become a non-negligible source of systematic error. We derive a framework that models the correlation induced by the window function and demonstrate this solution using both data from the first LIGO--Virgo transient catalog and simulated Gaussian noise.