论文标题

星系的动态表征最多$ z \ sim 7 $

Dynamical characterization of galaxies up to $z \sim 7$

论文作者

Rizzo, F., Kohandel, M., Pallottini, A., Zanella, A., Ferrara, A., Vallini, L., Toft, S.

论文摘要

Z〜7的星系动力学状态的表征对于约束驱动早期宇宙中质量组装的机制至关重要。但是,目前尚不清楚当前和未来观察的数据质量是否足以进行扎实的动力学分析。本文定义了对EOR的星系动力学状态的鲁棒表征所需的角度分辨率和S/N。最终目的是帮助设计针对原始星系排放线的空间分辨调查。我们研究了SERRA宇宙学模拟中Z〜6-7 lbgs的[CII] -158UM发射,涵盖了一系列动态状态:从磁盘到主要合并。我们创建具有各种数据质量的ALMA模拟观察结果,并应用文献中使用的运动学分类方法。这些测试使我们能够量化此类方法的性能,这是角度分辨率和S/N的函数。我们发现,几乎没有分辨的观察结果不允许对星系的正确动力学表征,从而导致样本中所有磁盘的分类错误。但是,即使使用典型的高Z星系的数据质量使用空间分辨的观测值,基于矩图的分析,标准运动学分类方法也无法将合并与磁盘区分开。仅用于少数明亮的星系就可以成功地应用这些标准方法的高角度分辨率和S/N可以成功应用这些标准方法。我们提出了一种称为PVSPLIT的新分类方法,该方法使用三个经验参数量化位置速度图中的不对称和形态特征。我们在模拟数据上测试PVSPLIT,结论是,只要S/N $ \ GTRSIM10 $,它可以预测星系是磁盘还是合并,并且主要轴是由$ \ gtrsim3 $独立分辨率元素覆盖的。

The characterization of the dynamical state of galaxies up to z~7 is crucial for constraining the mechanisms driving the mass assembly in the early Universe. However, it is unclear whether the data quality of current and future observations is sufficient to perform a solid dynamical analysis. This paper defines the angular resolution and S/N required for a robust characterization of the dynamical state of galaxies up to the EoR. The final aim is to help design spatially-resolved surveys targeting emission lines of primeval galaxies. We investigate the [CII]-158um emission from z~6-7 LBGs from the SERRA cosmological simulation, covering a range of dynamical states: from disks to major mergers. We create ALMA mock observations with various data quality and apply the kinematic classification methods used in the literature. These tests allow us to quantify the performances of such methods as a function of angular resolution and S/N. We find that barely-resolved observations do not allow the correct dynamical characterization of a galaxy, resulting in the misclassification of all disks in our sample. However, even when using spatially-resolved observations with data quality typical of high-z galaxies, the standard kinematic classification methods, based on the analysis of the moment maps, fail to distinguish a merger from a disk. The high angular resolution and S/N needed to apply these standard methods successfully can be achieved with current data only for a handful of bright galaxies. We propose a new classification method, called PVsplit, that quantifies the asymmetries and morphological features in position-velocity diagrams using three empirical parameters. We test PVsplit on our mock data concluding that it can predict whether a galaxy is a disk or a merger provided that S/N $\gtrsim10$, and the major axis is covered by $\gtrsim3$ independent resolution elements.

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