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arXiv 1003.5754astro-ph.COgr-qchep-th
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冷暗物质加速宇宙学和团簇形成的限制

Constraints on Cold Dark Matter Accelerating Cosmologies and Cluster Formation

S. Basilakos, J. A. S. Lima

摘要:

我们讨论了均匀和各向同性的平坦宇宙学的性质,其中目前的加速阶段仅由引力诱导的冷暗物质(CCDM)粒子($Ω_{m}=1$)的产生提供动力。对于文献中提出的一些物质产生率,我们证明了主要的宇宙学函数,如宇宙的尺度因子、哈勃膨胀率、生长因子和团簇形成率的解析定义。最好的CCDM方案只有一个自由参数,我们的联合分析涉及BAO + CMB + SNe Ia数据产生${\tildeΩ}_{m}= 0.28\pm 0.01$($1σ$),其中$\tilde{Ω}_{m}$是观测到的物质密度参数。特别是,这意味着该模型没有暗能量,但有效聚集的物质部分与大尺度结构的最新测定结果非常一致。在这种情况下,扰动的增长和星系团的形成也进行了研究。尽管事实上,这两种情况下可能共享相同的哈勃膨胀,我们发现,物质创造宇宙学预测更强的小尺度动力学,这意味着更快的增长速度的扰动相对于通常的$Λ$ CDM宇宙学。这样的结果表明,通过涉及CMB、弱透镜以及大尺度结构的更详细的分析,可能会对CCDM进行一次关键的观测测试,以$Λ$ CDM情景。

英文摘要:

We discuss the properties of homogeneous and isotropic flat cosmologies in which the present accelerating stage is powered only by the gravitationally induced creation of cold dark matter (CCDM) particles ($Ω_{m}=1$). For some matter creation rates proposed in the literature, we show that the main cosmological functions such as the scale factor of the universe, the Hubble expansion rate, the growth factor and the cluster formation rate are analytically defined. The best CCDM scenario has only one free parameter and our joint analysis involving BAO + CMB + SNe Ia data yields ${\tildeΩ}_{m}= 0.28\pm 0.01$ ($1σ$) where $\tilde{Ω}_{m}$ is the observed matter density parameter. In particular, this implies that the model has no dark energy but the part of the matter that is effectively clustering is in good agreement with the latest determinations from large scale structure. The growth of perturbation and the formation of galaxy clusters in such scenarios are also investigated. Despite the fact that both scenarios may share the same Hubble expansion, we find that matter creation cosmologies predict stronger small scale dynamics which implies a faster growth rate of perturbations with respect to the usual $Λ$CDM cosmology. Such results point to the possibility of a crucial observational test confronting CCDM with $Λ$CDM scenarios trough a more detailed analysis involving CMB, weak lensing, as well as the large scale structure.

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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