一种有效的符号切换暗能量：两种相互作用流体的Lotka-Volterra模型
An Effective Sign Switching Dark Energy: Lotka-Volterra Model of Two Interacting Fluids
AI总结：
本文用Lotka-Volterra方程建模两种相互作用暗能量流体，提出竞争与转化模型，证明可实现AdS到dS转变并穿越幽灵分界线，从而缓解哈勃张力和S_8张力。
摘要：
近年来解决哈勃张力和S_8张力的尝试之一，是考虑宇宙并非始于类似德西特（de Sitter）的时空，而是始于类似反德西特（anti-de Sitter）的时空。也就是说，宇宙在某个时刻经历了一次“AdS到dS”的转变。我们研究了存在两种暗能量流体的可能性，其中一种流体导致了类似反德西特的早期宇宙。二者之间的相互作用由Lotka-Volterra方程建模，该方程常用于种群生物学。我们考虑了“竞争”模型，并进一步将其分为“不公平竞争”和“公平竞争”两类。前者涉及一个与幽灵场（phantom）竞争的 quintessence 场，后者涉及两个幽灵流体。令人惊讶的是，即使在后者情形下，整体暗能量也有可能穿越幽灵分界线。后一模型还允许具有常数w的“AdS到dS”转变，从而规避了此类暗能量必须具有奇异状态方程这一结论。我们还考虑了一种“转化”模型，其中一个幽灵流体即使在被转化为负能量密度的 quintessence 时，仍能实现“AdS到dS”转变。在这些模型中，晚期有效暗能量的能量密度与流体的二次自相互作用项系数相关，这类似于种群生物学中的资源容量。
英文摘要：
One of the recent attempts to address the Hubble and $S_8$ tensions is to consider the Universe started out not as a de Sitter-like spacetime, but rather anti-de Sitter-like. That is, the Universe underwent an "AdS-to-dS" transition at some point. We study the possibility that there are two dark energy fluids, one of which gave rise to the anti-de Sitter-like early Universe. The interaction is modeled by the Lotka-Volterra equations, commonly used in population biology. We consider "competition" models that are further classified as "unfair competition" and "fair competition". The former involves a quintessence in competition with a phantom, and the second involves two phantom fluids. Surprisingly, even in the latter scenario it is possible for the overall dark energy to cross the phantom divide. The latter model also allows a constant $w$ "AdS-to-dS" transition, thus evading the theorem that such a dark energy must possess a singular equation of state. We also consider a "conversion" model in which a phantom fluid still manages to achieve "AdS-to-dS" transition even if it is being converted into a negative energy density quintessence. In these models, the energy density of the late time effective dark energy is related to the coefficient of the quadratic self-interaction term of the fluids, which is analogous to the resource capacity in population biology.
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