论文标题

引力波数据中具有非平稳噪声的参数估计

Parameter Estimation with Nonstationary Noise in Gravitational-wave Data

论文作者

Kumar, Sumit, Nitz, Alexander H., Forteza, Xisco Jiménez

论文摘要

重力波(GW)探测器的灵敏度的特征在于它们的噪声曲线,这些曲线确定了检测器的覆盖范围和能够准确测量天体物理源参数的能力。对于许多实际目的,检测器噪声通常被建模为固定和高斯,其功率光谱密度(PSD)的特征。但是,由于环境和工具因素,检测器状态的身体变化可能会将非平稳性引入噪声中。噪声行为的误容直接影响信号参数的后宽度。对于依赖于准确定位量的研究,它成为一个问题,例如i)使用星系的互相关方法探测宇宙学参数(例如,哈勃常数),ii)ii)使用来自Pre-Merger数据的参数估计(PE)进行电磁随访。我们研究动态噪声对GW事件PE的影响。我们通过估计沿潜在信号的时频轨迹归一化的局部有效的pseudo-PSD来开发一种新方法来纠正动态噪声。我们通过在各种情况下注入二进制中子星(BNS)合并信号来进行模拟,在这些情况下,检测器经历了第三代探测器的参考噪声曲线(宇宙探索器,爱因斯坦望远镜)的参考噪声曲线。例如,对于一个来源,噪声误导的噪声偏向信号到噪声估计值什至$ 10 \%$,人们希望估计的天空本地化将被$ \ sim 20 \%$降低或过度报告;这样的错误,尤其是在低延迟的情况下,可能会导致后续活动错过实际的源位置。

The sensitivity of gravitational-wave (GW) detectors is characterized by their noise curves, which determine the detector's reach and ability to measure the parameters of astrophysical sources accurately. The detector noise is typically modeled as stationary and Gaussian for many practical purposes and is characterized by its Power Spectral Density (PSD). However, due to environmental and instrumental factors, physical changes in the state of detectors may introduce non-stationarity into the noise. Misestimation of the noise behavior directly impacts the posterior width of the signal parameters. It becomes an issue for studies that depend on accurate localization volumes, such as i) probing cosmological parameters (e.g., Hubble constant) using cross-correlation methods with galaxies, ii) doing electromagnetic follow-up using localization information from parameter estimation (PE) done from pre-merger data. We study the effects of dynamical noise on the PE of the GW events. We develop a new method to correct dynamical noise by estimating a locally valid pseudo-PSD normalized along a potential signal's time-frequency track. We do simulations by injecting binary neutron star (BNS) merger signals in various scenarios where the detector goes through a period of non-stationarity with reference noise curves of third-generation detectors (Cosmic Explorer, Einstein telescope). As an example, for a source where mis-modeling of the noise biases the signal-to-noise estimate by even $10\%$, one would expect the estimated sky localization to be either under or over-reported by $\sim 20\%$; errors like this, especially in low-latency, could potentially cause follow-up campaigns to miss the actual source location.

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