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arXiv 1806.09477astro-ph.CO
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模拟星表和协方差矩阵近似方法的比较I:关联函数

Comparing approximate methods for mock catalogues and covariance matrices I: correlation function

Martha Lippich, Ariel G. Sánchez, Manuel Colavincenzo, Emiliano Sefusatti, Pierluigi Monaco, Linda Blot, Martin Crocce, Marcelo A. Alvarez, Aniket Agrawal, Sant… 展开作者

Martha Lippich, Ariel G. Sánchez, Manuel Colavincenzo, Emiliano Sefusatti, Pierluigi Monaco, Linda Blot, Martin Crocce, Marcelo A. Alvarez, Aniket Agrawal, Santiago Avila, Andrés Balaguera-Antolínez, Richard Bond, Sandrine Codis, Claudio Dalla Vecchia, Antonio Dorta, Pablo Fosalba, Albert Izard, Francisco-Shu Kitaura, Marcos Pellejero-Ibanez, George Stein, Mohammadjavad Vakili, Gustavo Yepes

摘要:

本文是第一次在一组分析的协方差矩阵的聚类统计的引力结构形成的几种近似方法。本文主要研究各向异性两点关联函数测量的协方差矩阵。我们的比较包括七种近似方法,可以分为三类:确定性地跟踪线性密度场演化的预测方法(ICE-COLA、Peak Patch和Pinocchio),需要使用N体模拟进行校准的方法(Patchy and Halogen)和更简单的配方的基础上的假设的概率分布函数(PDF)的形状的密度波动(对数正态和高斯密度场)。我们分析的影响,使用协方差估计从这些近似方法获得的星系团测量的宇宙学分析,作为参考的协方差推断从一组完整的N体模拟。我们发现,所有的近似方法都可以准确地恢复使用N体协方差推断的平均参数值。所获得的参数不确定性通常同意相应的N体的结果在5%内为我们的较低的质量阈值,和10%为我们的较高的质量阈值。此外,我们发现,某些方法的约束条件可以相差高达20%,这取决于用于定义协方差矩阵的晕圈样本是否通过匹配父N体样本的质量、数量密度或聚类幅度来定义。我们的配置空间分析的结果表明,最近似的方法提供了类似的结果,没有一种方法明显优于其他。

英文摘要:

This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, Peak Patch, and Pinocchio), methods that require a calibration with N-body simulations (Patchy and Halogen), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (log-normal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5% for our lower mass threshold, and 10% for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20% depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others.

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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