论文标题
白矮人二进制调制可以帮助随机重力波背景搜索
White dwarf binary modulation can help stochastic gravitational wave background search
论文作者
论文摘要
对于以Milli-Hz频段为中心的随机引力背景（SGWBS）搜索，在银河系中由白矮人二进制室（WDB）产生的银河前景污染了半乳酸外信号。由于WDB的各向异性分布模式以及Spaceborne重力波干涉仪星座的运动，时间域数据流将显示年度调制。该属性与SGWB的属性根本不同。在这封信中，我们根据年度调制现象为数据向量提出了一种新的过滤方法。我们将所得的逆方差过滤器应用于LISA数据挑战。结果表明，对于较弱的SGWB信号，例如能量密度$ω_ {\ rm astro} = 1 \ times10^{ - 12} $，滤波方法可以突出地增强后验分布峰。对于更强的信号，例如$ω_ {\ rm astro} = 3 \ times10^{ - 12} $，该方法可以将贝叶斯证据从“实质性”提高到对无效假设的“实质性”。该方法是独立于模型的和独立的。除了重力波数据外，它不要求其他类型的信息。
For the stochastic gravitational wave backgrounds (SGWBs) search centred at the milli-Hz band, the galactic foreground produced by white dwarf binaries (WDBs) within the Milky Way contaminates the extra-galactic signal severely. Because of the anisotropic distribution pattern of the WDBs and the motion of the spaceborne gravitational wave interferometer constellation, the time-domain data stream will show an annual modulation. This property is fundamentally different from those of the SGWBs. In this Letter, we propose a new filtering method for the data vector based on the annual modulation phenomenon. We apply the resulted inverse variance filter to the LISA data challenge. The result shows that for the weaker SGWB signal, such as energy density $Ω_{\rm astro}=1\times10^{-12}$, the filtering method can enhance the posterior distribution peak prominently. For the stronger signal, such as $Ω_{\rm astro}=3\times10^{-12}$, the method can improve the Bayesian evidence from `substantial' to `strong' against null hypotheses. This method is model-independent and self-contained. It does not ask for other types of information besides the gravitational wave data.
