Title: ASTErIsM - Application of topometric clustering algorithms in automatic galaxy detection and classification Show Chinese title

Title: 恒星座 - 拓扑聚类算法在自动星系探测与分类中的应用

Abstract: We present a study on galaxy detection and shape classification using topometric clustering algorithms. We first use the DBSCAN algorithm to extract, from CCD frames, groups of adjacent pixels with significant fluxes and we then apply the DENCLUE algorithm to separate the contributions of overlapping sources. The DENCLUE separation is based on the localization of pattern of local maxima, through an iterative algorithm which associates each pixel to the closest local maximum. Our main classification goal is to take apart elliptical from spiral galaxies. We introduce new sets of features derived from the computation of geometrical invariant moments of the pixel group shape and from the statistics of the spatial distribution of the DENCLUE local maxima patterns. Ellipticals are characterized by a single group of local maxima, related to the galaxy core, while spiral galaxies have additional ones related to segments of spiral arms. We use two different supervised ensemble classification algorithms, Random Forest, and Gradient Boosting. Using a sample of ~ 24000 galaxies taken from the Galaxy Zoo 2 main sample with spectroscopic redshifts, and we test our classification against the Galaxy Zoo 2 catalog. We find that features extracted from our pipeline give on average an accuracy of ~ 93%, when testing on a test set with a size of 20% of our full data set, with features deriving from the angular distribution of density attractor ranking at the top of the discrimination power. Show Chinese abstract

Abstract: 我们研究了使用拓扑聚类算法进行星系检测和形状分类的方法。 首先，我们使用DBSCAN算法从CCD帧中提取具有显著流量的相邻像素组，然后应用DENCLUE算法分离重叠源的贡献。 DENCLUE分离基于局部最大值模式的定位，通过一个迭代算法，该算法将每个像素分配给最近的局部最大值。 我们的主要分类目标是区分椭圆星系和螺旋星系。 我们引入了一组新的特征，这些特征来源于像素组形状的几何不变矩计算以及DENCLUE局部最大值模式的空间分布统计。 椭圆星系由与星系核相关的单个局部最大值组组成，而螺旋星系则有额外的局部最大值组，与螺旋臂段相关。 我们使用两种不同的监督集成分类算法，即随机森林和梯度提升。 使用来自星系动物园2主样本的约24000个星系样本，并测试了我们的分类方法与星系动物园2目录的一致性。 我们发现，从我们的流程中提取的特征，在测试集上平均准确率为~93%，测试集大小为完整数据集的20%，其中基于密度吸引子角部分布的特征具有最高的鉴别能力。