arXivDaily arXiv每日学术速递 周一至周五更新
北美退伍军人节(Veterans Day),12 日无更新
arXiv 1907.06540gr-qcastro-ph.HEastro-ph.IM
收藏

噪声谱估计方法及其对致密双星合并引力波测量的影响

Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers

Katerina Chatziioannou, Carl-Johan Haster, Tyson B. Littenberg, Will M. Farr, Sudarshan Ghonge, Margaret Millhouse, James A. Clark, Neil Cornish

摘要:

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。特别地,用于引力波数据分析的最常用的似然函数假设噪声是高斯的、平稳的并且具有已知的频率依赖方差。在计算似然函数之前,将有色高斯噪声的方差用作对数据的白化滤波器。在实践中,噪声方差是未知的,并且它在几十秒到几分钟的时间尺度上演变。我们研究了两种方法来估计这个白化滤波器的地基引力波探测器的目标进行参数估计研究。第一种方法使用从我们希望分析的特定段分离的大量数据,并通过均值-中值Welch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,其潜在地包括引力波信号,并且通过在样条和洛伦兹的总和方面拟合数据的功率谱来获得白化滤波器。比较了这两种方法,认为后者对引力波参数估计更为可靠。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑