Avsajanishvili Olga, Huang Yiwen, Samushia Lado, Kahniashvili Tina
1Abastumani Astrophysical Observatory, Ilia State University, 3-5 Cholokashvili Ave., 0194 Tbilisi, Georgia.
Department of Physics, University of California, San Diego, La Jolla, CA 92093 USA.
Eur Phys J C Part Fields. 2018;78(9):773. doi: 10.1140/epjc/s10052-018-6233-y. Epub 2018 Sep 26.
Most dark energy models have the CDM as their limit, and if future observations constrain our universe to be close to CDM Bayesian arguments about the evidence and the fine-tuning will have to be employed to discriminate between the models. Assuming a baseline CDM model we investigate a number of quintessence and phantom dark energy models, and we study how they would perform when compared to observational data, such as the expansion rate, the angular distance, and the growth rate measurements, from the upcoming Dark Energy Spectroscopic Instrument (DESI) survey. We sample posterior likelihood surfaces of these dark energy models with Monte Carlo Markov Chains while using central values consistent with the Planck CDM universe and covariance matrices estimated with Fisher information matrix techniques. We find that for this setup the Bayes factor provides a substantial evidence in favor of the CDM model over most of the alternatives. We also investigated how well the CPL parametrization approximates various scalar field dark energy models, and identified the location for each dark energy model in the CPL parameter space.
大多数暗能量模型都以冷暗物质(CDM)模型作为其极限情况。如果未来的观测结果表明我们的宇宙接近CDM模型,那么就必须运用关于证据和微调的贝叶斯论证来区分不同的模型。假设一个基线CDM模型,我们研究了一些精质和幽灵暗能量模型,并探讨了与即将开展的暗能量光谱仪(DESI)巡天所获取的观测数据(如膨胀率、角距离和增长率测量值)相比时,这些模型的表现如何。我们使用蒙特卡罗马尔可夫链对这些暗能量模型的后验似然面进行采样,同时采用与普朗克CDM宇宙一致的中心值以及用费舍尔信息矩阵技术估计的协方差矩阵。我们发现,对于这种设置,贝叶斯因子为支持CDM模型而非大多数其他模型提供了大量证据。我们还研究了CPL参数化对各种标量场暗能量模型的近似程度,并确定了每个暗能量模型在CPL参数空间中的位置。