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arXiv 2104.14065gr-qcastro-ph.CO
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使用H（z）和Pantheon数据拟合具有$Λ$ CDM限制的$f(Q,T)$重力模型

Fitting $f(Q,T)$ gravity models with a $Λ$CDM limit using H(z) and Pantheon data

Antonio Nájera, Amanda Fajardo

备注：
V3: Accepted version in Physics of the Dark Universe. Minor changes plus corrections in the results of the sixth model
发表信息：
Physics of the Dark Universe, Volume 34, December 2021, 100889
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摘要：

我们提出了五个$f(Q,T)$模型，它们是对称远程平行引力的扩展，其中$Q$是非度量度，$T$是应力-能量张量的迹。通过取其参数的特定值，这些模型具有$Λ$ CDM限制。使用宇宙计时器和超新星Ia数据，我们发现，我们的模型是一致的$Λ$ CDM在95%的置信水平。为了看看这些模型中的一个是否可以从背景角度挑战$Λ$ CDM，我们计算了它们和$Λ$ CDM的贝叶斯证据。根据它，一致性模型优于其中的四个，显示出对$f(Q,T) = -Q/G_N + bT$和$f(Q,T) = -(Q+2Λ)/G_N +bT$的弱偏好，对$f(Q,T) = -(Q+2 H_0^2 c (Q/(6H_0^2))^{n+1})/G_N + bT $的显著偏好，以及对$f(Q,T) = -(Q+2H_0^2c(Q/(6H_0^2))^{n+1} + 2Λ)/G_N + bT$的强烈偏好。有趣的是，包括$T^2$依赖性（$f(Q,T) = -(Q+2Λ)/G_N - ((16π)^2 G_N b)/(120 H_0^2) T^2$）的模型显示出对$Λ$ CDM的{实质}偏好。{因此，我们鼓励进一步分析这个模型，以测试其在背景视角之外的可行性。

英文摘要：

We proposed five $f(Q,T)$ models, which are an extension of symmetric teleparallel gravity, where $Q$ is the non-metricity and $T$ is the trace of the stress-energy tensor. By taking specific values of their parameters, these models have a $Λ$CDM limit. Using cosmic chronometers and supernovae Ia data, we found that our models are consistent with $Λ$CDM at a 95\% confidence level. To see whether one of these models can challenge $Λ$CDM at a background perspective, we computed the Bayesian evidence for them and $Λ$CDM. According to it, the concordance model is preferred over four of them, showing a weak preference against $f(Q,T) = -Q/G_N + bT$ and $f(Q,T) = -(Q+2Λ)/G_N +bT$, a substantial preference against $f(Q,T) = -(Q+2 H_0^2 c (Q/(6H_0^2))^{n+1})/G_N + bT $, and a strong preference against $f(Q,T) = -(Q+2H_0^2c(Q/(6H_0^2))^{n+1} + 2Λ)/G_N + bT$. Interestingly, a model includying a $T^2$ dependence ($f(Q,T) = -(Q+2Λ)/G_N - ((16π)^2 G_N b)/(120 H_0^2) T^2$) showed a {substantial} preference against $Λ$CDM. {Therefore, we encourage further analyses of this model to test its viability outside the background perspective.}

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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