arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2107.11539astro-ph.CO
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基于$χ^2$分布的宇宙学数据的非参数建模

Non-parametric modeling of the cosmological data, base on the $χ^2$ distribution

Maryam Vazirnia, Ahmad Mehrabi

摘要:

在$Λ$ CDM模型中,对晚期和近期宇宙的宇宙学观测揭示了当前宇宙膨胀速率中令人困惑的$\sim 4.5σ$张力。除了建议解决紧张局势的各种情况外,非参数建模可能会提供有用的见解。在本文中,我们看看三个著名的非参数方法,平滑方法,遗传算法和高斯过程。考虑到这三种方法,我们利用最新的哈勃参数数据重建宇宙膨胀率和超新星Pantheon样本重建光度距离。与文献中的类似研究相比,卡方分布已被用于构建一个可靠的标准来选择重建。最后,我们计算宇宙膨胀($H_0$)的每一种方法的当前速率,提供了一些关于每种方法的性能的讨论,并比较结果。

英文摘要:

In the $Λ$CDM model, cosmological observations from the late and recent universe reveal a puzzling $\sim 4.5σ$ tension in the current rate of universe expansion. In addition to the various scenarios suggested to resolve the tension, non-parametric modeling may provide useful insights. In this paper, we look at three well-known non-parametric methods, the smoothing method, the genetic algorithm, and the Gaussian process. Considering these three methods, we employ the recent Hubble parameters data to reconstruct the rate of universe expansion and supernovae Pantheon sample to reconstruct the luminosity distance. In contrast to the similar studies in the literature, the chi-squared distribution has been used to construct a reliable criterion to select a reconstruction. Finally, we compute the current rate of universe expansion ($H_0$) for each method, provide some discussions regarding the performance of each approach, and compare the results.

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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