标题： 探测类星体Ly$α$吸收线分布的非高斯谱 显示英文标题

标题： Detecting the non-Gaussian Spectrum of QSO's Ly$α$ Absorption Line Distribution

摘要： 我们分析了类星体吸收光谱中 Ly$\alpha$森林线分布中的非高斯性。对该数据进行的统计检验表明，即使在大尺度上 Ly$\alpha$线分布的功率谱被发现是平坦的，也可能存在大尺度结构。显然，高于二阶的统计量对于量化 Ly$\alpha$云的聚类行为至关重要。通过对三个独立的 Ly$\alpha$森林数据集应用离散小波变换，我们发现 Ly$\alpha$森林的分布确实表现出从 5 到 10 h$^{-1}$Mpc 的非高斯行为，置信度大于 95%。在大尺度上可用的两个数据集在更大的尺度上也被发现是非高斯的。这些技术在区分 Ly$\alpha$森林形成的模型方面非常有效，这些模型在二阶和更低阶统计量上是退化的（简写）。 显示英文摘要

摘要： We present an analysis of the non-Gaussianity in the distribution of Ly$\alpha$ forest lines in the QSO absorption spectra. Statistical tests performed on this data indicate that there may be large scale structure even though the power spectrum of the Ly$\alpha$ line distribution on large scales is found to be flat. It is apparent that higher (than two) order statistics are crucial in quantifying the clustering behavior of Ly$\alpha$ clouds. Using the discrete wavelet on three independent data sets of Ly$\alpha$ forests, we find that the distribution of Ly$\alpha$ forests does show non-Gaussian behavior on scales from 5 to 10 h$^{-1}$ Mpc with confidence level larger than 95%. Two data sets available on large scales are found to be non-Gaussian on even larger scales. These techniques are effective in discriminating among models of the Ly$\alpha$ forest formation, which are degenerate at second and lower order statistics (abridged).