论文标题

部分可观测时空混沌系统的无模型预测

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

论文作者

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

论文摘要

三阶弱透镜统计是宇宙学分析的有前途的工具,因为它们在宇宙大规模结构的非高西语中提取宇宙学信息。但是,此类分析需要协方差的精确模型。在有关三阶弱透镜统计系列的第二篇论文中,我们得出了三阶孔径统计的协方差的分析模型$ \ langle m_ \ mathrm {ap}^3 \ rangle $。我们从$ \ langle m_ \ mathrm {ap}^3 \ rangle $的真实空间估计器中得出协方差模型。我们通过将模型与模拟高斯随机场(GRF)和两组N体模拟的估计进行比较来验证该模型。最后,我们使用模型协方差和模拟估计进行模拟宇宙学分析,以比较产生的参数约束。对于GRF和$ n $ body模拟,我们发现模型和模拟之间的良好协议。从我们的协方差模型中的$ S_8 $ - $ω__\ MATHRM {M} $平面中的标准数在从模拟协方差获得的$ 3 \%之内。我们还表明,我们的模型基于使用收敛图的估计器,可用于获得基于三点剪切相关函数的估计器的协方差的上限和下限。现实的调查数据需要第二个估计器。在我们的派生中,我们发现$ \ langle m_ \ mathrm {ap}^3 \ rangle $ $协方差无法从Bispectrum协方差获得,并且其中包括几个“有限端口术语”,这些“有限场术语”与不相反的调查区域不扩展。我们的协方差模型足以分析III期调查。傅立叶空间中统计数据的协方差不能总是直接转化为实现真实空间统计的协方差。该建模代码可在https://github.com/sheydenreich/threepoint/releases/上获得。

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/ .

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源