arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2207.09079astro-ph.COgr-qc
收藏

相互作用暗能量:新参数化与观测约束

Interacting Dark Energy: New parametrization and observational constraints

Arkajit Aich

AI总结:

本文提出一种新的暗物质稀释参数化来描述暗物质与暗能量相互作用,并结合 Pantheon 超新星和哈勃数据约束模型参数,进而分析宇宙演化及粒子物理含义。

摘要:

我们基于一种新参数化重新研究了涉及暗物质与暗能量相互作用的宇宙学。该新参数化基于如下假设:当暗物质与暗能量发生相互作用时,暗物质的稀释方式将不同于标准的非相互作用情形。我们用这一新参数化重建了宇宙学方程。通过使用来自 Pantheon 的超新星数据和哈勃数据,我们还获得了对传统宇宙学参数和新参数的观测约束。得到的参数值为 $H_0$ = 69.023 $\pm$ 0.722,$M$ = -19.385 $\pm$ 0.019,$I$ = 2.901 $\pm$ 0.092 以及 $Ω_{dm0}(1 - \frac{3}{I})\frac{1}{κ}$ = 0.254 $\pm$ 0.023,其中 $H_0$、$M$、$Ω_{dm0}$ 和 $κ$ 分别是哈勃常数、Ia 型超新星的绝对星等、当前暗物质密度以及暗物质与暗能量之间的耦合参数,而 $I$ 是我们引入模型中的一个新参数,称为稀释参数,表示相互作用情形下暗物质的修正稀释。我们还深入探讨了该模型在宇宙演化、减速参数、宇宙年龄以及相互作用情形的粒子物理含义等方面的物理特征,并得出了结论。

英文摘要:

We have re-investigated Cosmology involving interaction between Dark matter and Dark Energy in the light of a new parametrization. The new parametrization is based on the hypothesis that when Dark matter and Dark Energy will interact, Dark matter will dilute in a different manner than standard non-interacting scenario. We re-built the Cosmological equations with this new parametrization. Observational constraints on the traditional Cosmological parameters and new parameters has also been obtained by using supernova data from Pantheon and Hubble data. The parameter values obtained are $H_0$ = 69.023 $\pm$ 0.722, $M$ = -19.385 $\pm$ 0.019, $I$ = 2.901 $\pm$ 0.092 and $Ω_{dm0}(1 - \frac{3}{I})\frac{1}κ$ = 0.254 $\pm$ 0.023 where $H_0$, $M$, $Ω_{dm0}$ and $κ$ are Hubble constant, absolute magnitude of type 1a supernova, present day dark matter density and coupling parameter between dark matter and dark energy respectively while $I$ is a new parameter, dubbed dilution parameter which we introduced in the model representing the modified dilution of dark matter in the interacting scenario. The physical features of the model in regard to evolution of the Universe, deceleration parameter, age of Universe, particle physics implications of interacting scenario has also been explored in depth and conclusions has been drawn.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑