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arXiv 2212.04485astro-ph.CO
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三阶剪切统计量宇宙学参数分析路线图 II:解析协方差估计

A roadmap to cosmological parameter analysis with third-order shear statistics II: Analytic covariance estimate

Laila Linke, Sven Heydenreich, Pierre A. Burger, Peter Schneider

AI总结:

本文推导并验证了三阶孔径质量统计量 $\langle M_\mathrm{ap}^3\rangle$ 的解析协方差模型,经 GRF 与 N 体模拟检验,其 $S_8$-$\Omega_\mathrm{m}$ 优值误差小于3%,可支撑 stage III 巡天分析。

摘要:

三阶弱引力透镜统计量是宇宙学分析的一种有前景的工具,因为它们能够提取宇宙大尺度结构非高斯性中所含的宇宙学信息。然而,此类分析需要精确且准确的协方差模型。在这篇关于三阶弱引力透镜统计量系列论文的第二篇中,我们推导并验证了一个用于三阶孔径统计量 $\langle M_\mathrm{ap}^3\rangle$ 协方差的解析模型。我们从 $\langle M_\mathrm{ap}^3\rangle$ 的实空间估计量出发推导该协方差模型。通过将其与来自模拟高斯随机场(GRF)和两组 N 体模拟的估计结果进行比较,我们对模型进行了验证。最后,我们分别使用模型协方差和模拟估计协方差开展模拟宇宙学分析,以比较由此得到的参数约束。我们发现,无论对于 GRF 还是 N 体模拟,模型与模拟结果均吻合良好。由我们的协方差模型得到的 $S_8$-$\Omega_\mathrm{m}$ 平面内的优值(figure-of-merit)与由模拟协方差所得结果的偏差在 3% 以内。我们还表明,基于使用会聚图的估计量所建立的模型,可用于获得基于三点剪切相关函数的估计量协方差的上界和下界;后一种估计量是实际巡天数据所必需的。在推导过程中,我们发现 $\langle M_\mathrm{ap}^3\rangle$ 协方差无法由双谱协方差得到,并且它包含若干不随巡天面积倒数缩放的“有限视场项”。我们的协方差模型对于分析第三阶段(stage III)巡天具有足够的精度。傅里叶空间统计量的协方差并非总能直接转换为实空间统计量的协方差。建模代码可在 https://github.com/sheydenreich/threepoint/releases/ 获取。

英文摘要:

Third-order weak lensing statistics are a promising tool for cosmological analyses since they extract cosmological information in the non-Gaussianity of the cosmic large-scale structure. However, such analyses require precise and accurate models for the covariance. In this second paper of a series on third-order weak lensing statistics, we derive and validate an analytic model for the covariance of the third-order aperture statistics $\langle M_\mathrm{ap}^3\rangle$. We derive the covariance model from a real-space estimator for $\langle M_\mathrm{ap}^3\rangle$. We validate the model by comparing it to estimates from simulated Gaussian random fields (GRF) and two sets of N-body simulations. Finally, we perform mock cosmological analyses with the model covariance and the simulation estimate to compare the resulting parameter constraints. We find good agreement between the model and the simulations, both for the GRF and the $N$-body simulations. The figure-of-merit in the $S_8$-$Ω_\mathrm{m}$ plane from our covariance model is within 3\% of the one obtained from the simulated covariances. We also show that our model, which is based on an estimator using convergence maps, can be used to obtain upper and lower bounds for the covariance of an estimator based on three-point shear correlation functions. This second estimator is required for realistic survey data. In our derivation, we find that the $\langle M_\mathrm{ap}^3\rangle$ covariance cannot be obtained from the bispectrum covariance and that it includes several `finite-field terms' that do not scale with the inverse survey area. Our covariance model is sufficiently accurate for analysing stage III surveys. Covariances for statistics in Fourier space cannot always be straightforwardly converted into covariance for real-space statistics. The modelling code is available at https://github.com/sheydenreich/threepoint/releases/ .

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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