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Parameter Estimation in Searches for the Stochastic Gravitational-Wave Background

机译:搜索随机引力波背景时的参数估计

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摘要

The stochastic gravitational-wave background (SGWB) is expected to arise from the superposition of many independent and unresolved gravitational-wave signals of either cosmological or astrophysical origin. The spectral content of the SGWB carries signatures of the physics that generated it. We present a Bayesian framework for estimating the parameters associated with different SGWB models using data from gravitational-wave detectors. We apply this technique to recent results from LIGO to produce the first simultaneous 95% confidence level limits on multiple parameters in generic power-law SGWB models and in SGWB models of compact binary coalescences. We also estimate the sensitivity of the upcoming second-generation detectors such as Advanced LIGO or Virgo to these models and demonstrate how SGWB measurements can be combined and compared with observations of individual compact binary coalescences in order to build confidence in the origin of an observed SGWB signal. In doing so, we demonstrate a novel means of differentiating between different sources of the SGWB.
机译:随机引力波背景(SGWB)可能是由于宇宙学或天体起源的许多独立且未解析的引力波信号的叠加而产生的。 SGWB的光谱内容带有产生它的物理特征。我们提出了一种贝叶斯框架,用于使用引力波探测器的数据估算与不同SGWB模型相关的参数。我们将此技术应用于LIGO的最新结果,以在通用幂律SGWB模型和紧凑型二元合并的SGWB模型中对多个参数产生第一个同时95%的置信度限制。我们还估计了即将到来的第二代检测器(如Advanced LIGO或Virgo)对这些模型的敏感性,并演示了如何将SGWB测量值结合起来并与单个紧凑型二元合并观测结果进行比较,从而建立对观测到的SGWB起源的信心。信号。通过这样做,我们展示了一种区分SGWB不同来源的新颖方法。

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