论文标题

偏向CMB $ \ times $ LSS:BISPECTRUM分析的快速方法

Skewing the CMB$\times$LSS: a Fast Method for Bispectrum Analysis

论文作者

Chakraborty, Priyesh, Chen, Shu-Fan, Dvorkin, Cora

论文摘要

即将到来的宇宙微波背景(CMB)镜头测量值和层析成像星系调查预计将在未来几年为我们提供高精度的数据集,从而为富有成果的互相关分析铺平了道路。在本文中,我们研究了加权偏度 - 光谱的信息含量,这是角度双光谱振幅的几乎最佳估计器,是从与CMB镜头相互交叉相交的星系相交的银河系中提取偏置和宇宙学参数的非高斯信息的一种手段,同时又可以在快速方面加速。我们的结果表明,对于Planck卫星和暗能量光谱仪(DESI)的结合,偏斜谱和Bispectrum的偏见和宇宙学参数的约束差异最多为$ 17 \%$。我们进一步比较并发现我们的理论偏斜光谱与从N体模拟估计的一致性之间的一致性,其中重要的是要在扰动理论之外包括引力非线性和CMB镜头后出生的效果。 We define an algorithm to apply the skew-spectrum estimator to the data and, as a preliminary step, we use the skew-spectra to constrain bias parameters and the amplitude of shot noise from the simulations through a Markov chain Monte Carlo likelihood analysis, finding that it may be possible to reach percent-level estimates for the linear bias parameter $b_1$.

Upcoming cosmic microwave background (CMB) lensing measurements and tomographic galaxy surveys are expected to provide us with high-precision data sets in the coming years, thus paving the way for fruitful cross-correlation analyses. In this paper we study the information content of the weighted skew-spectrum, a nearly-optimal estimator of the angular bispectrum amplitude, as a means to extract non-Gaussian information on both bias and cosmological parameters from the bispectra of galaxies cross-correlated with CMB lensing, while gaining significantly on speed. Our results show that for the combination of the Planck satellite and the Dark Energy Spectroscopic Instrument (DESI), the difference in the constraints on bias and cosmological parameters from the skew-spectrum and the bispectrum is at most $17\%$. We further compare and find agreement between our theoretical skew-spectra and those estimated from N-body simulations, for which it is important to include gravitational non-linearities beyond perturbation theory and the post-Born effect for CMB lensing. We define an algorithm to apply the skew-spectrum estimator to the data and, as a preliminary step, we use the skew-spectra to constrain bias parameters and the amplitude of shot noise from the simulations through a Markov chain Monte Carlo likelihood analysis, finding that it may be possible to reach percent-level estimates for the linear bias parameter $b_1$.

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