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arXiv 2011.05969gr-qcastro-ph.IM
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各向异性随机引力波背景的统一成图

Unified mapmaking for an anisotropic stochastic gravitational wave background

Jishnu Suresh, Anirban Ain, Sanjit Mitra

摘要:

一个随机的引力波背景(SGWB),由未解决的天体物理源的信号叠加产生,可能会在未来几年内检测到。因此,估计整个天空的强度变化可以在提高我们对天体物理模型的理解方面发挥关键作用。为先进的地面干涉测量探测器的所有数据采集作业制作了天空图。虽然这些地图是在像素和SPH基地,探测,分别,本地化和扩散天体物理学和宇宙学的来源,与算法,采用互相关作为共同的策略,基本的代数和数值实现仍然不同。因此,在这些分析中,需要在两个基地制作天空图。我们表明,这些明显冗余的方法确实可以统一到一个单一的分析,可以探测非常不同的尺度,并通过将它们应用于真实数据来证明它。我们首先发展了代数,以表明在两个不同的基础上的结果是容易转换的。然后,我们将这两种方案合并到各向异性SGWB PyStoch的标准分析管道中。这将使得在SpH基础上的SGWB各向异性搜索也能够充分利用集成的\hpx工具,并且使得在每个频率仓中执行搜索在计算上是可行的。然而,我们遵循不同的方法直接估计的SpH时刻。我们表明,从这些不同的方法得到的结果匹配得很好,差异小于$0.1$ \%的SpH矩和小于$0.01$ \%的Fisher信息矩阵。因此,我们得出结论,一个单一的天空图将足以描述在随机背景的各向异性。PyStoch的多种功能将有助于估计和约束表征各向异性背景的各种度量。

英文摘要:

A stochastic gravitational wave background (SGWB), created by the superposition of signals from unresolved astrophysical sources, may be detected in the next few years. Estimating the variation of intensity across the sky can, therefore, play a key role in improving our understanding of astrophysical models. Skymaps have been produced for all the data-taking runs of the advanced ground-based interferometric detectors. While these maps are being produced in pixel and SpH bases, to probe, respectively, localized and diffuse astrophysical and cosmological sources, with algorithms that employ cross-correlation as the common strategy, the underlying algebra and numerical implementation remain different. As a consequence, there was a need for producing skymaps in both bases in those analyses. We show that these manifestly redundant methods could indeed be unified to a single analysis that can probe very different scales and demonstrate it by applying them on real data. We first develop the algebra to show that the results in two different bases are easily transformable. We then incorporate both the schemes in the now-standard analysis pipeline for anisotropic SGWB, PyStoch. This will enable SGWB anisotropy searches in SpH basis also to take full advantage of integrated \hpx tools and makes it computationally feasible to perform the search in every frequency bin. We, however, follow a different approach for direct estimation of the SpH moments. We show that the results obtained from these different methods match very well; the differences are less than $0.1$\% for the SpH moments and less than $0.01$\% for the Fisher information matrices. Thus we conclude that a single skymap will be sufficient to describe the anisotropies in a stochastic background. The multiple capabilities of PyStoch will be useful for estimating and constraining various measures that characterize an anisotropic background.

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。

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