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arXiv 2409.14780astro-ph.GAastro-ph.CO
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利用尘埃约束暗物质模型

Using dust to constrain dark matter models

Adam Ussing, Robert Mostoghiu Paun, Darren Croton, Celine Boehm, Alan Duffy, Chris Power

AI总结:

该研究通过银河系型暗晕的流体动力学放大模拟,在匹配卫星星系数量后比较CDM与3.5 keV WDM,发现二者尘埃总量和径向分布差异显著,提出尘埃可作为区分暗物质模型的独特观测探针。

摘要:

在本文中,我们使用银河系型暗晕的流体动力学放大模拟,探索将尘埃作为观测示踪剂,以区分冷暗物质宇宙与温暗物质(WDM)宇宙。通过比较冷暗物质粒子模型和3.5 keV WDM粒子模型,我们在模拟中利用可变的超新星率调节星系形成效率,从而在保持所有其他模拟参数不变的情况下,产生具有相似卫星星系族群的银河系系统。冷暗物质(CDM)具有更多子结构,因此需要比WDM更高的超新星效率才能达到相同的卫星星系数量。这些不同的超新星效率会在其宿主星系周围产生不同的尘埃分布;我们通过使用Powderday代码库对模拟输出进行后处理来生成这些尘埃分布。分析每个模拟中得到的尘埃后,我们发现CDM银河系暗晕中的尘埃约为WDM中的4.5倍。随后,我们研究了尘埃延伸至$R_{200\ ext{c}}$的分布,结果表明WDM模拟的集中度明显低于对应的CDM模拟,尽管子结构差异使比较变得复杂。我们的结果表明,尘埃是检验暗物质理论的一种可能的独特探针。

英文摘要:

In this paper, we use hydrodynamic zoom-in simulations of Milky Way-type haloes to explore using dust as an observational tracer to discriminate between cold and warm dark matter (WDM) universes. Comparing a cold and 3.5 keV WDM particle model, we tune the efficiency of galaxy formation in our simulations using a variable supernova rate to create Milky Way systems with similar satellite galaxy populations while keeping all other simulation parameters the same. Cold dark matter (CDM), having more substructure, requires a higher supernova efficiency than WDM to achieve the same satellite galaxy number. These different supernova efficiencies create different dust distributions around their host galaxies, which we generate by post-processing the simulation output with the \powderday{} codebase. Analysing the resulting dust in each simulation, we find $\sim$4.5 times more dust in our CDM Milky Way haloes compared with WDM. The distribution of dust out to $R_{200\text{c}}$ is then explored, revealing that the WDM simulations are noticeably less concentrated than their CDM counterparts, although differences in substructure complicate the comparison. Our results indicate that dust is a possible unique probe to test theories of dark matter.

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。

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