论文标题
通过测量精细结构常数来区分冰冻和解冻暗能量模型
Distinguishing freezing and thawing dark energy models through measurements of the fine-structure constant
论文作者
论文摘要
映射暗能量的行为是观察宇宙学的一项紧迫任务。现象学分类将动态暗能模型分为冰冻和融化,具体取决于状态的暗能量方程是接近还是偏离$ W = p/ρ= -1 $。此外,在现实的动态暗能模型中,动态自由度有望将其与电磁扇区息息,从而导致精细结构常数$α$的变化。我们讨论了区分具有当前和即将发生的观察设施的冻结和融化模型的可行性,并使用Mukhanov作为基金会范式引入的状态的暗能量方程的参数化。我们说明了冻结和解冻模型如何导致$α$的不同红移依赖性,并结合当前的天体物理观察结果和本地实验来限制此类模型,尽管考虑了比以前的研究中使用的一项更大的扩展参数空间,但对键耦合参数的限制提高了两倍以外的限制。我们还简要讨论了未来设施预期的改进,并就此类参数化的实际限制发表了评论。特别是,我们表明,足够敏感的数据可以区分冰冻模型和解冻模型,至少在假设相关参数空间不包括幻影深色能量模型的情况下。
Mapping the behaviour of dark energy is a pressing task for observational cosmology. Phenomenological classification divides dynamical dark energy models into freezing and thawing, depending on whether the dark energy equation of state is approaching or moving away from $w=p/ρ=-1$. Moreover, in realistic dynamical dark energy models the dynamical degree of freedom is expected to couple to the electromagnetic sector, leading to variations of the fine-structure constant $α$. We discuss the feasibility of distinguishing between the freezing and thawing classes of models with current and forthcoming observational facilities and using a parametrisation of the dark energy equation of state, which can have either behaviour, introduced by Mukhanov as fiducial paradigm. We illustrate how freezing and thawing models lead to different redshift dependencies of $α$, and use a combination of current astrophysical observations and local experiments to constrain this class of models, improving the constraints on the key coupling parameter by more than a factor of two, despite considering a more extended parameter space than the one used in previous studies. We also briefly discuss the improvements expected from future facilities and comment on the practical limitations of this class of parametrisations. In particular, we show that sufficiently sensitive data can distinguish between freezing and thawing models, at least if one assumes that the relevant parameter space does not include phantom dark energy models.