论文标题

ly $α$森林断层扫描的IgM状态方程的新颖估计量

A Novel Estimator for the Equation of State of the IGM by Ly$α$ Forest Tomography

论文作者

Müller, Hendrik, Behrens, Christoph, Marsh, David James Edward

论文摘要

我们提出了一个新的程序,以根据ly $α$森林层析成像的准线性结构形成状态估算层间介质的状态方程,并将其应用于Redshift $ Z = 2.5 $的UVE \ _SQUAD调查中的21个高质量的类星体光谱。我们的估计是基于对视线的完整层合截面的。我们使用两种不同的反转算法,迭代高斯 - 纽顿方法和正则化概率保护方法逆转数据,这些方法取决于不同的先验,并比较反转导致通量空间和密度空间。这样,我们的方法将通量空间中吸收曲线的拟合与对物质分布的先验知识的恢复密度分布的分析结合在一起。我们的估计比现有估计值更精确,尤其是在小型红移箱上。特别是,我们将温度密度与功率定律建模,并在平均密度$ t_0 = 13400 = 13400 = {+1700} _ { - 1300} \,\ Mathrm {k} $以及power power(polytropic index)$γ= 1.42 \ pm pm 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.11 $ 0.此外,我们测量一个光电离率$γ_ { - 12} = 1.1^{+0.16} _ { - 0.17} $。将公开使用所使用的反转技术的实现。

We present a novel procedure to estimate the Equation of State of the intergalactic medium in the quasi-linear regime of structure formation based on Ly$α$ forest tomography and apply it to 21 high quality quasar spectra from the UVES\_SQUAD survey at redshift $z=2.5$. Our estimation is based on a full tomographic inversion of the line of sight. We invert the data with two different inversion algorithms, the iterative Gauss-Newton method and the regularized probability conservation approach, which depend on different priors and compare the inversion results in flux space and in density space. In this way our method combines fitting of absorption profiles in flux space with an analysis of the recovered density distributions featuring prior knowledge of the matter distribution. Our estimates are more precise than existing estimates, in particular on small redshift bins. In particular, we model the temperature-density relation with a power law and observe for the temperature at mean density $T_0 = 13400^{+1700}_{-1300}\,\mathrm{K}$ and for the slope of the power-law (polytropic index) $γ= 1.42 \pm 0.11$ for the power-law parameters describing the temperature-density relation. Moreover, we measure an photoionization rate $Γ_{-12} = 1.1^{+0.16}_{-0.17}$. An implementation of the inversion techniques used will be made publicly available.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源