Adaptive modeling of correlated noise in space-based gravitational wave detectors

IF 3.6 3区 物理与天体物理 Q2 ASTRONOMY & ASTROPHYSICS
Ya-Nan Li, Yi-Ming Hu and En-Kun Li
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引用次数: 0

Abstract

Accurately estimating the statistical properties of noise is important in data analysis for space-based gravitational wave (GW) detectors. Noise in different time-delay interferometry channels correlates with each other. Many studies often assume uncorrelated noise and ignore the off-diagonal elements in the noise covariance matrix. This could lead to some bias in the parameter estimation of GW signals. In this paper, we present a framework for reconstructing the full noise covariance matrix, including frequency-dependent auto- and cross-correlated power spectral densities, without assuming the parametric analytic expressions of the noise model. Our approach combines spline interpolation with trigonometric basis functions to construct a semi-analytical representation of the noise. We then employ trans-dimensional Bayesian inference to fit the correlated noise structure. The resulting software package, NOISAR, successfully recovers both auto- and cross-correlated power spectral features with a relative error of about 10%.
天基引力波探测器相关噪声的自适应建模
准确估计噪声的统计性质是天基引力波探测器数据分析的重要内容。不同时延干涉信道中的噪声是相互关联的。许多研究通常假设噪声不相关,忽略了噪声协方差矩阵中的非对角线元素。这可能会导致GW信号的参数估计存在一定的偏差。在本文中,我们提出了一个框架来重建完整的噪声协方差矩阵,包括频率相关的自相关和交叉相关的功率谱密度,而不假设噪声模型的参数解析表达式。我们的方法结合样条插值和三角基函数来构造噪声的半解析表示。然后我们使用跨维贝叶斯推理来拟合相关的噪声结构。所得软件包NOISAR成功地恢复了自相关和交叉相关的功率谱特征,相对误差约为10%。
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来源期刊
Classical and Quantum Gravity
Classical and Quantum Gravity 物理-天文与天体物理
CiteScore
7.00
自引率
8.60%
发文量
301
审稿时长
2-4 weeks
期刊介绍: Classical and Quantum Gravity is an established journal for physicists, mathematicians and cosmologists in the fields of gravitation and the theory of spacetime. The journal is now the acknowledged world leader in classical relativity and all areas of quantum gravity.
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