论文标题
通过自然进化的暗能量：使用近似贝叶斯计算来限制暗能量
Dark energy by natural evolution: Constraining dark energy using Approximate Bayesian Computation
论文作者
论文摘要
我们通过近似贝叶斯计算（ABC）和较晚的宇宙学观察来从生物学启发的观点看黑能。我们发现，在标准的$λ$ CDM宇宙学场景上，动态的暗能量最高或自然选择的ABC语言。我们确认这一结论对于是否考虑了重气尾声振荡和哈勃恒定先验。我们的结果表明，该算法更喜欢哈勃常数的低值，一致或至少几个标准偏差，而与宇宙微波背景估计值相比，无论最初在每个模型中最初采用的先验如何。这支持了传统的MCMC分析的结果，并且可以看作是加强动态暗能量的证据，是更有利的晚期宇宙学模型。
We look at dark energy from a biology inspired viewpoint by means of the Approximate Bayesian Computation (ABC) and late time cosmological observations. We find that dynamical dark energy comes out on top, or in the ABC language naturally selected, over the standard $Λ$CDM cosmological scenario. We confirm this conclusion is robust to whether baryon acoustic oscillations and Hubble constant priors are considered. Our results show that the algorithm prefers low values of the Hubble constant, consistent or at least a few standard deviation away from the cosmic microwave background estimate, regardless of the priors taken initially in each model. This supports the result of the traditional MCMC analysis and could be viewed as strengthening evidence for dynamical dark energy being a more favorable model of late time cosmology.
