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arXiv 1011.1982gr-qcastro-ph.CO
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用最新的Union2超新星数据检验宇宙加速

Examining the cosmic acceleration with the latest Union2 supernova data

Zhengxiang Li, Puxun Wu, Hongwei Yu

摘要:

本文利用Chevallier-Polarski-Linder(CPL)参数化方法,通过重建最新的Union 2 Ia型超新星样本的$Om$诊断参数和减速参数$q$,以及重子声学振荡(BAO)和宇宙微波背景(CMB),研究了宇宙膨胀的历史。我们得到Union 2 +BAO在$z<0.3$处的加速度越小越有利于膨胀.然而,一旦在分析中加入CMB数据,宇宙加速度仍在增加,表明低红移数据和高红移数据之间存在紧张关系。为了显著降低这种张力,考虑了两种不同的方法,因此选择了Union 2的两个不同的子样本。然后我们发现,当忽略系统误差时,两个不同的子样本+BAO+CMB对宇宙膨胀历史给出了完全不同的结果,其中一个表明宇宙加速度在减小,另一个正好相反,尽管它们都单独与BAO一起支持宇宙加速度在减慢。然而,一旦考虑到系统误差,联盟2的两个不同的子样本以及BAO和CMB都有利于增加目前的宇宙加速度。因此,关于宇宙加速是否正在减慢的明确答案需要更一致的数据和更可靠的方法来分析它们。

英文摘要:

In this Letter, by reconstructing the $Om$ diagnostic and the deceleration parameter $q$ from the latest Union2 Type Ia supernova sample with and without the systematic error along with the baryon acoustic oscillation (BAO) and the cosmic microwave background (CMB), we study the cosmic expanding history, using the Chevallier-Polarski-Linder (CPL) parametrization. We obtain that Union2+BAO favor an expansion with a decreasing of the acceleration at $z<0.3$. However, once the CMB data is added in the analysis, the cosmic acceleration is found to be still increasing, indicating a tension between low redshift data and high redshift one. In order to reduce this tension significantly, two different methods are considered and thus two different subsamples of Union2 are selected. We then find that two different subsamples+BAO+CMB give completely different results on the cosmic expanding history when the systematic error is ignored, with one suggesting a decreasing cosmic acceleration, the other just the opposite, although both of them alone with BAO support that the cosmic acceleration is slowing down. However, once the systematic error is considered, two different subsamples of Union2 along with BAO and CMB all favor an increasing of the present cosmic acceleration. Therefore a clear-cut answer on whether the cosmic acceleration is slowing down calls for more consistent data and more reliable methods to analyze them.

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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