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微扰水平下的广义相对论熵加速:CLASS实现及首个玻尔兹曼编码约束

General Relativistic Entropic Acceleration at the perturbation level: a CLASS implementation and first Boltzmann-code constraints

Simone D'Onofrio, Dong Ha Lee, Eleonora Di Valentino, Juan García-Bellido

arXiv 2607.25841首次发表:更新:

AI 中文总结

研究广义相对论熵加速(GREA)在微扰水平的情况,通过在爱因斯坦 - 玻尔兹曼求解器中实现,结合马尔可夫链蒙特卡罗分析,对耦合\(\alpha\)进行约束,结果与理论相符,还得到与\(\Lambda\)CDM匹配度高且有独特状态方程预测的结果。

AI 中文摘要

广义相对论熵加速(GREA)将宇宙的晚期加速归因于因果宇宙学视界的熵增长,无需宇宙学常数,其唯象学由单个\(\mathcal{O}(1)\)参数\(\alpha\)确定。该模型迄今仅在背景水平上面临数据。我们在爱因斯坦 - 玻尔兹曼求解器中首次实现它:GREA背景直接集成到CLASS中,熵分量作为由参数化后弗里德曼方案调节的有效流体演化,可获取完整的CMB和物质功率谱。通过COBAYA针对完整的原初CMB似然性、DESI DR2 BAO和Ia型超新星进行马尔可夫链蒙特卡罗分析,约束耦合\(\alpha \sim 1\),与理论预测高度一致,尽管增加了一个自由参数,但拟合与\(\Lambda\)CDM在\(|\Delta\chi^2| \lesssim 6\)内匹配。从数据推断的状态方程与分箱的、与模型无关的重建一致,并在\(z \simeq 2\)处呈现幻影分界线的第二次穿越,这是热力学动力学而非强加参数化的独特预测。

英文摘要

General Relativistic Entropic Acceleration (GREA) attributes the late-time acceleration of the Universe to the entropy growth of the causal cosmological horizon, without a cosmological constant, with a phenomenology fixed by the single $\mathcal{O}(1)$ parameter $α$. The model has so far been confronted with data only at the background level. We present its first implementation within an Einstein-Boltzmann solver: the GREA background is integrated directly into CLASS, while the entropic component is evolved as an effective fluid regulated by the parametrized-post-Friedmann scheme, giving access to the full CMB and matter power spectra. A Markov-chain Monte Carlo analysis with COBAYA against the full primary-CMB likelihoods, DESI DR2 BAO and Type Ia supernovae constrains the coupling $α\sim 1$, in excellent agreement with the theoretical prediction, with a fit matching $Λ$CDM to within $|Δχ^2| \lesssim 6$ despite the addition of a single free parameter. The equation of state inferred from the data agrees with binned, model-independent reconstructions and exhibits a second crossing of the phantom divide at $z \simeq 2$, a distinctive prediction of the thermodynamic dynamics rather than of an imposed parametrization.

Comments21 pages, 15 figures

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