论文标题
关于降低维度降低和聚类算法的应用，用于分类星系的运动形态
On the application of dimensionality reduction and clustering algorithms for the classification of kinematic morphologies of galaxies
论文作者
论文摘要
星系的形态学分类被认为是一个相关问题，可以从不同的角度解决。天文数据集的大小和准确性的增长增加，它需要使用自动方法执行这些分类。这项工作的目的是提出和评估一种自动无监督星系运动形态的分类方法，该分类产生有意义的聚类并捕获星系的基本特性的变化。我们从鹰项目的最大仿真中获得了2064个星系样品的运动学图，该图像模仿了积分田间光谱（IFS）图像。这些地图是维数还原算法的输入，然后是聚类算法。我们分析了从该过程中应用于不同输入的群集中物理和观察参数的变化。本文所研究的输入是（a）在固定倾斜倾斜下观察到的整个星系样本的视线速度图，（b）视线速度，分布和磁通图一起，用于整个星系样本，在固定斜率上观察到的星系样本，（c）斜线，（c）两种分散的速度，分散型，分散式磁带，分散型，弗洛克斯，弗洛克斯，弗洛克斯，弗洛克斯，弗拉克斯，弗洛克斯，弗拉克斯，弗洛克斯的摩擦。旋转和（d）视线速度，分散和通量图一起，用于混合不同观察角的星系。该方法仅在视线速度图中的应用实现了缓慢的旋转器（SRS）和快速旋转器（FRS）之间的明确划分，并且可以区分旋转方向。通过在输入处添加分散和通量信息，低旋转边缘星系根据其形状分开。简略。
The morphological classification of galaxies is considered a relevant issue and can be approached from different points of view. The increasing growth in the size and accuracy of astronomical data sets brings with it the need for the use of automatic methods to perform these classifications. The aim of this work is to propose and evaluate a method for automatic unsupervised classification of kinematic morphologies of galaxies that yields a meaningful clustering and captures the variations of the fundamental properties of galaxies. We obtain kinematic maps for a sample of 2064 galaxies from the largest simulation of the EAGLE project that mimics integral field spectroscopy (IFS) images. These maps are the input of a dimensionality reduction algorithm followed by a clustering algorithm. We analyse the variation of physical and observational parameters among the clusters obtained from the application of this procedure to different inputs. The inputs studied in this paper are (a) line-of-sight velocity maps for the whole sample of galaxies observed at fixed inclinations, (b) line-of-sight velocity, dispersion, and flux maps together for the whole sample of galaxies observed at fixed inclinations, (c) line-of-sight velocity, dispersion, and flux maps together for two separate subsamples of edge-on galaxies with similar amount of rotation, and (d) line-of-sight velocity, dispersion, and flux maps together for galaxies from different observation angles mixed. The application of the method to solely line-of-sight velocity maps achieves a clear division between slow rotators (SRs) and fast rotators (FRs) and can differentiate rotation orientation. By adding the dispersion and flux information at the input, low rotation edge-on galaxies are separated according to their shapes. Abridged.
