arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2407.04890gr-qchep-th
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具有体黏度的对称遥平行引力中的宇宙学约束

Cosmological constraints in symmetric teleparallel gravity with bulk viscosity

Dheeraj Singh Rana, P. K. Sahoo

AI总结:

提出含体黏度的幂律 $f(Q)$ 宇宙学模型,利用 CC+Pantheon+SH0ES 数据与贝叶斯 MCMC 约束参数,诊断表明其呈现精质型晚期加速特征。

摘要:

在本研究中,我们在修正的 $f(Q)$ 引力框架内探索宇宙的加速膨胀。研究聚焦于体黏度在理解宇宙加速膨胀中的作用。具体而言,我们考虑了一个体黏性物质主导的宇宙学模型,其体黏度系数表示为 $ζ=ζ_0ρH^{-1}+ζ_1H$。我们采用幂律 $f(Q)$ 函数 $f(Q)=αQ^n$,其中 $α$ 和 $n$ 为任意常数,并推导了平坦 FLRW 度规下场方程的解析解。随后,我们使用 Cosmic Chronometers(CC)+Pantheon+SH0ES 组合样本来估计所得解析解的自由参数。我们通过似然函数和 MCMC 随机抽样技术,并结合 AIC 和 BIC 统计评估准则,进行贝叶斯统计分析以估计后验概率。此外,我们还探索了重要宇宙学参数的演化行为。有效状态方程(EOS)参数预测了宇宙膨胀阶段的加速行为。进一步地,通过 statefinder 和 $Om(z)$ 诊断检验,我们发现我们的黏性模型支持精质型行为,并能够成功描述晚期宇宙情景。

英文摘要:

In this study, we explore the accelerated expansion of the universe within the framework of modified $f(Q)$ gravity. The investigation focus on the role of bulk viscosity in understanding the universe's accelerated expansion. Specifically, a bulk viscous matter-dominated cosmological model is considered, with the bulk viscosity coefficient expressed as $ζ= ζ_0 ρH^{-1} + ζ_1 H $. We consider the power law $f(Q)$ function $f(Q)=αQ^n $, where $α$ and $n$ are arbitrary constants and derive the analytical solutions for the field equations corresponding to a flat FLRW metric. Subsequently, we used the combined Cosmic Chronometers (CC)+Pantheon+SH0ES sample to estimate the free parameters of the obtained analytic solution. We conduct Bayesian statistical analysis to estimate the posterior probability by employing the likelihood function and the MCMC random sampling technique, along with the AIC and BIC statistical assessment criteria. In addition, we explore the evolutionary behavior of significant cosmological parameters. The effective equation of state (EOS) parameter predicts the accelerating behavior of the cosmic expansion phase. Further, by the statefinder and $Om(z)$ diagnostic test, we found that our viscous model favors quintessence-type behavior and can successfully describe the late-time scenario.

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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