Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers
Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers
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DOI：
10.1103/physrevd.100.104004
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发表时间：
2019-07
影响因子：
5
通讯作者：
K. Chatziioannou;C. Haster;T. Littenberg;W. Farr;S. Ghonge;M. Millhouse;J. Clark;N. Cornish
中科院分区：
文献类型：
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作者：
K. Chatziioannou;C. Haster;T. Littenberg;W. Farr;S. Ghonge;M. Millhouse;J. Clark;N. Cornish
估计地面探测器探测到的引力波信号的参数需要了解探测器噪声的特性。特别是，用于引力波数据分析的最常用的似然函数假定噪声是高斯的、平稳的并且具有已知的频率相关方差。在计算似然函数之前，将有色高斯噪声的方差用作数据的白化过滤器。实际上，噪声的变化是未知的，它在几十秒到几分钟的时间尺度上演变。我们研究了两种估计地面引力波探测器白化滤波的方法，目的是进行参数估计研究。第一种方法使用从我们想要分析的特定分段中分离出来的大量数据，并通过均值-中值韦尔奇方法计算噪声的功率谱密度。第二种方法使用与参数估计分析相同的数据段，潜在地包括引力波信号，并通过对数据的功率谱进行样条和洛伦兹和的拟合来获得白化滤波器。我们对这两种方法进行了比较，认为后者更适合于引力波参数估计。
Estimating the parameters of gravitational wave signals detected by ground-based detectors requires an understanding of the properties of the detectors' noise. In particular, the most commonly used likelihood function for gravitational wave data analysis assumes that the noise is Gaussian, stationary, and of known frequency-dependent variance. The variance of the colored Gaussian noise is used as a whitening filter on the data before computation of the likelihood function. In practice the noise variance is not known and it evolves over timescales of dozens of seconds to minutes. We study two methods for estimating this whitening filter for ground-based gravitational wave detectors with the goal of performing parameter estimation studies. The first method uses large amounts of data separated from the specific segment we wish to analyze and computes the power spectral density of the noise through the mean-median Welch method. The second method uses the same data segment as the parameter estimation analysis, which potentially includes a gravitational wave signal, and obtains the whitening filter through a fit of the power spectrum of the data in terms of a sum of splines and Lorentzians. We compare these two methods and argue that the latter is more reliable for gravitational wave parameter estimation.