论文标题

lyman- $α$森林相关的Alcock-Paczyński效应:合成数据的分析验证

The Alcock-Paczyński effect from Lyman-$α$ forest correlations: Analysis validation with synthetic data

论文作者

Cuceu, Andrei, Font-Ribera, Andreu, Martini, Paul, Joachimi, Benjamin, Nadathur, Seshadri, Rich, James, González-Morales, Alma X., Bourboux, Hélion du Mas des, Farr, James

论文摘要

Ly $α$森林的三维分布已广泛用于通过测量Baryon声学振荡(BAO)量表来限制宇宙学。但是,可以通过Alcock-Paczyński(AP)效应从Ly $α$森林相关的完整形状中提取更多宇宙学信息。在这项工作中,我们通过研究扩展的Baryon振荡光谱调查(EBOSS)的合成数据来准备宇宙学分析$α$森林相关性的全部形状。为了验证这种分析,我们使用一百个EBOSS合成数据集。这些模拟经历了与真实数据相同的分析过程。我们对从一百个eBoss实现测得的相关函数的平均值进行全面分析,并发现我们的LY $α$相关模型在当前数据集上的性能很好。我们表明,我们能够获得$ d_m/d_h(z_ \ mathrm {eff})$的无偏全形测量,其中$ d_m $是横向comoving距离,$ d_h $是hubble的距离,$ d_h $是$ z__ \ z_ \ zyrm {eff} $是测量的有效redshift。我们在一系列秤上测试拟合,并决定使用$ r_ \ mathrm {min} = 25 \ h^{ - 1} \ text {mpc} $的最小分离。我们还研究和讨论影响$α$森林相关性的主要污染物的影响,并提出有关如何使用真实数据进行此类分析的建议。虽然最终的eBoss ly $α$ BAO分析测量$ d_m/d_h(z_ \ mathrm {eff} = 2.33)$,$ 4 \%$ $统计精度,但相同相关的完整形状拟合可能会提供$ \ sim2 \%$ $的测量。

The three-dimensional distribution of the Ly$α$ forest has been extensively used to constrain cosmology through measurements of the baryon acoustic oscillations (BAO) scale. However, more cosmological information could be extracted from the full shapes of the Ly$α$ forest correlations through the Alcock-Paczyński (AP) effect. In this work, we prepare for a cosmological analysis of the full shape of the Ly$α$ forest correlations by studying synthetic data of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We use a set of one hundred eBOSS synthetic data sets in order to validate such an analysis. These mocks undergo the same analysis process as the real data. We perform a full-shape analysis on the mean of the correlation functions measured from the one hundred eBOSS realizations, and find that our model of the Ly$α$ correlations performs well on current data sets. We show that we are able to obtain an unbiased full-shape measurement of $D_M/D_H(z_\mathrm{eff})$, where $D_M$ is the transverse comoving distance, $D_H$ is the Hubble distance, and $z_\mathrm{eff}$ is the effective redshift of the measurement. We test the fit over a range of scales, and decide to use a minimum separation of $r_\mathrm{min}=25\ h^{-1}\text{Mpc}$. We also study and discuss the impact of the main contaminants affecting Ly$α$ forest correlations, and give recommendations on how to perform such analysis with real data. While the final eBOSS Ly$α$ BAO analysis measured $D_M/D_H(z_\mathrm{eff}=2.33)$ with $4\%$ statistical precision, a full-shape fit of the same correlations could provide a $\sim2\%$ measurement.

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