arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1809.00282astro-ph.COastro-ph.GA
收藏

用层叠凹透镜约束暗能量

Constraining Dark Energy With Stacked Concave Lenses

Fuyu Dong, Jun Zhang, Yu Yu, Xiaohu Yang, Hekun Li, Jiaxin Han, Wentao Luo, Jiajun Zhang, Liping Fu

摘要:

低密度区受非线性结构形成和重子物理的影响较小。它们是探测暗能量本质的理想场所,暗能量是宇宙加速的一种可能解释。与需要识别单个空洞的空洞透镜不同,我们研究了低密度位置(LDP)周围的堆叠透镜信号,LDP被定义为在投影中没有前景明亮星系的地方。该方法允许直接比较与数值计算结果绘制明亮的星系晕之间的对应关系。它导致了透镜信号,这些信号足够重要,可以区分几种暗能量模型。在这项工作中,我们使用CFHTLenS目录来定义LDP,以及测量它们的背景透镜信号。我们考虑了几种不同的前景亮星系的定义(红移范围和星等切割)。关于宇宙学模型,我们运行了六个模拟:第一组模拟具有相同的初始条件,使用$\rm{w_{de}=-1,-0.5,-0.8,-1.2}$ ;第二组模拟包括略微不同的$Λ$ CDM模型和来自\cite{2017NatAs...1..627Z}的w(z)模型。透镜效应的结果表明,与$\rm{w_{de}=-0.5,-0.8}$的模型是不赞成的,和其他四个模型都达到了可比的协议与数据。

英文摘要:

Low density regions are less affected by the nonlinear structure formation and baryonic physics. They are ideal places for probing the nature of dark energy, a possible explanation for the cosmic acceleration. Unlike void lensing, which requires identifications of individual voids, we study the stacked lensing signals around the low-density-positions (LDP), defined as places that are devoid of foreground bright galaxies in projection. The method allows a direct comparison with numerical results by drawing correspondence between the bright galaxies with halos. It leads to lensing signals that are significant enough for differentiating several dark energy models. In this work, we use the CFHTLenS catalogue to define LDPs, as well as measuring their background lensing signals. We consider several different definitions of the foreground bright galaxies (redshift range \& magnitude cut). Regarding the cosmological model, we run six simulations: the first set of simulations have the same initial conditions, with $\rm{w_{de}=-1,-0.5,-0.8,-1.2}$; the second set of simulations include a slightly different $Λ$CDM model and a w(z) model from \cite{2017NatAs...1..627Z}. The lensing results indicate that the models with $\rm{w_{de}=-0.5,-0.8}$ are not favored, and the other four models all achieve comparable agreement with the data.

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。

↑