Clustering of the large scale structure provides complementary information to the measurements of the cosmic microwave background anisotropies through power spectrum and bispectrum of density perturbations. Extracting the bispectrum information, however, is more challenging than it is from the power spectrum due to the complex models and the computational cost to measure the signal and its covariance. To overcome these problems, we adopt a proxy statistic, skew spectrum which is a cross-spectrum of the density field and its quadratic field. By applying a large smoothing filter to the density field, we show the theory fits the simulations very well. With the spectra and their full covariance estimated from $N$-body simulations as our "mock" Universe, we perform a global fits for the cosmological parameters. The results show that adding skew spectrum to power spectrum the $1\sigma$ marginalized errors for parameters $ b_1^2A_s, n_s$ and $f_{\rm NL}^{\rm loc}$ are reduced by $31\%, 22\%, 44\%$, respectively. This is the answer to the question posed in the title and indicates that the skew spectrum will be a fast and effective method to access complementary information to that enclosed in the power spectrum measurements, especially for the forthcoming generation of wide-field galaxy surveys.

中文翻译：

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结合偏斜谱和功率谱我们可以学到什么？

大尺度结构的聚类通过功率谱和密度扰动双谱为宇宙微波背景各向异性的测量提供了补充信息。然而，由于复杂的模型和测量信号及其协方差的计算成本，提取双谱信息比从功率谱中提取更具挑战性。为了克服这些问题，我们采用了一种代理统计量，偏斜谱，它是密度场及其二次场的交叉谱。通过对密度场应用一个大的平滑滤波器，我们表明理论非常适合模拟。将根据 $N$-body 模拟估计的光谱及其完整协方差作为我们的“模拟”宇宙，我们对宇宙学参数进行全局拟合。结果表明，在功率谱中加入偏斜谱，参数$b_1^2A_s、n_s$和$f_{\rm NL}^{\rm loc}$的$1\sigma$边缘化误差减少了$31\%, 22\ %, 44\%$, 分别。这是标题中提出的问题的答案，并表明偏斜谱将是一种快速有效的方法来获取功率谱测量中包含的补充信息，特别是对于即将到来的宽视场星系调查。