反反应模型的贝叶斯分析
Bayesian analysis of the backreaction models
摘要：
我们提出了四种不同类型的backreation模型，这是基于Buchert方程的贝叶斯分析。在这种方法中，人们考虑一般物质分布的爱因斯坦方程的解，然后取各种可观测量的平均值。当这种方法被证明可以在不诉诸暗能量的情况下与观测结果达成一致时，它就引起了人们的极大兴趣。本文用SNIa、BAO和CMB数据比较了LambdaCDM模型和后作用模型，发现前者更好。然而，测试模型是基于一些特定的假设之间的关系，平均空间曲率和反作用，以及曲率和曲率指数之间的关系。在本文中，我们修改了后一个假设，保持前一个不变。我们发现，通过改变曲率和曲率指数之间的关系，我们可以获得更好的拟合。因此，仍然需要进一步的工作-特别是应该重新审视逆反应和曲率之间的关系，以便充分确定逆反应模型模拟暗能量的可行性。
英文摘要：
We present the Bayesian analysis of four different types of backreation models, which are based on the Buchert equations. In this approach, one considers a solution to the Einstein equations for a general matter distribution and then an average of various observable quantities is taken. Such an approach became of considerable interest when it was shown that it could lead to agreement with observations without resorting to dark energy. In this paper we compare the LambdaCDM model and the backreation models with SNIa, BAO, and CMB data, and find that the former is favoured. However, the tested models were based on some particular assumptions about the relation between the average spatial curvature and the backreaction, as well as the relation between the curvature and curvature index. In this paper we modified the latter assumption, leaving the former unchanged. We find that, by varying the relation between the curvature and curvature index, we can obtain a better fit. Therefore, some further work is still needed -- in particular the relation between the backreaction and the curvature should be revisited in order to fully determine the feasibility of the backreaction models to mimic dark energy.
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。
