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arXiv 2303.11271astro-ph.CO
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不同BAO数据集的模型选择结果-- DE模型和$Ω_K$ CDM

Model selection results from different BAO datasets -- DE models and $Ω_K$CDM

Denitsa Staicova

摘要:

使用重子声学振荡(BAO)数据集提供了一个独特的机会,连接早期宇宙和晚期宇宙。在这个过程中,我们讨论了最近的结果,使用边缘化的可能性,以消除$H_0-r_d $简并,然后测试它在不同的暗能量(DE)模型。发现这种方法不依赖于对$r_d$或$H_0$的校准,允许我们获得与用标准似然计算的结果相当的结果。在这里,我们强调的主要差异,我们观察到的两个不同的BAO数据集,我们雇用-横向的,只包含角度BAO测量,和混合的,包含角度和径向BAO测量。我们看到,这两个数据集对DE模型有不同的统计偏好,对宇宙曲率也有不同的偏好。

英文摘要:

The use of the baryonic acoustic oscillations (BAO) datasets offers a unique opportunity to connect the early universe and the late one. In this proceeding, we discuss recent results that used a marginalised likelihood to remove the $H_0-r_d $ degeneracy and then tested it on different dark energy (DE) models. It was found that this approach which does not rely on calibration on $r_d$ or $H_0$, allows us to obtain results, comparable to the ones calculated with standard likelihoods. Here we emphasize on the major differences that we observed for the two different BAO datasets that we employed -- a transversal one, containing only angular BAO measurements, and a mixed one, containing both angular and radial BAO measurements. We see that the two datasets have different statistical preferences for DE models and also different preference for the curvature of the universe.

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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