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arXiv 1608.04007astro-ph.CO
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通过信息场论从Ia超新星数据得到的宇宙膨胀历史--魅力码

Cosmic expansion history from SNe Ia data via information field theory -- the charm code

Natàlia Porqueres, Torsten A. Enßlin, Maksim Greiner, Vanessa Böhm, Sebastian Dorn, Pilar Ruiz-Lapuente, Alberto Manrique

摘要:

我们提出的魅力(宇宙历史不可知论重建方法),一种新的推理算法,重建编码在哈勃参数$H(z)$从超新星Ia数据的宇宙膨胀历史。该方法的新颖之处在于信息场论的使用,统计场论,是非常适合的最佳信号恢复算法的建设。魅力算法非参数化地推断出$s(a)=\ln(ρ(a)/ρ_{\mathrm{crit}0})$,即确定$H(z)$的密度演化,而不假设$ρ(a)$的解析形式,而仅假设其具有比例因子$a=(1+z)^{-1}$的平滑性。从数据中恢复信号$s(a)$的推理问题是制定在一个完全贝叶斯的方式。详细地说,我们将信号重写为背景宇宙学和扰动的总和。这使我们能够确定的最大后验估计的信号的迭代维纳滤波器的方法。应用魅力的Union 2.1超新星编译,我们已经恢复了宇宙膨胀的历史,是完全兼容的标准$Λ$ CDM宇宙膨胀的历史与普朗克任务的结果一致的参数值。

英文摘要:

We present charm (cosmic history agnostic reconstruction method), a novel inference algorithm that reconstructs the cosmic expansion history as encoded in the Hubble parameter $H(z)$ from SNe Ia data. The novelty of the approach lies in the usage of information field theory, a statistical field theory that is very well suited for the construction of optimal signal recovery algorithms. The charm algorithm infers non-parametrically $s(a)=\ln(ρ(a)/ρ_{\mathrm{crit}0})$, the density evolution which determines $H(z)$, without assuming an analytical form of $ρ(a)$ but only its smoothness with the scale factor $a=(1+z)^{-1}$. The inference problem of recovering the signal $s(a)$ from the data is formulated in a fully Bayesian way. In detail, we have rewritten the signal as the sum of a background cosmology and a perturbation. This allows us to determine the maximum a posteriory estimate of the signal by an iterative Wiener filter method. Applying charm to the Union2.1 supernova compilation, we have recovered a cosmic expansion history that is fully compatible with the standard $Λ$CDM cosmological expansion history with parameter values consistent with the results of the Planck mission.

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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