VEXAS：辅助调查的VISTA扩展--数据发布2：南半球源的基于机器学习的分类
VEXAS: VISTA EXtension to Auxiliary Surveys -- Data Release 2: Machine-learning based classification of sources in the Southern Hemisphere
摘要：
我们提出了VISTA扩展到辅助调查（VEXAS）的第二个公共数据发布（DR），在那里我们根据机器学习算法的集合将物体分类为恒星，星系和类星体。VEXAS的目的是建立最广泛的多波长目录，为大量的科学用途提供参考星等、颜色和形态信息。我们应用了32种不同的机器学习模型，基于三种不同的算法和不同的幅度集，训练样本和三个VEXAS DR 1光学+红外（IR）表的分类问题。这些表是在DR 1中创建的，它将VISTA近红外数据与WISE远红外数据以及来自暗能量巡天（VEXAS-DESW）、天空制图巡天（VEXAS-SMW）和PanSTARRS（VEXAS-PSW）的光学星等进行交叉匹配。我们组装了一个大表的光谱确认的对象（415 628个独特的对象），基于我们用于训练的6个不同的光谱调查的组合。我们开发的特征插补分类也在一个或多个波段的幅度丢失的对象。我们在南半球总共对约9000万个物体进行了分类。其中，~ 62.9 M（~ 52.6 M）被归类为“高置信度”（“安全”）恒星，~ 920 K（~ 750 K）被归类为“高置信度”（“安全”）类星体，~ 34.8 M（~ 34.1 M）被归类为“高置信度”（“安全”）星系，概率为$p_{\rm class}\ge 0.7$（$p_{\rm class}\ge 0.9$）。高置信度河外天体的密度随勘测深度变化很大：在$p_{\rm class}\ge 0.7$，在VEXAS-DESW足迹中有111个/deg $^2$类星体，在VEXAS-PSW足迹中有103个/deg $^2$，而在VEXAS-SM足迹中只有10.7个/deg $^2$。需要改进中红外的深度以及光学和近红外的覆盖范围，以用于尚未被DESW和PSW覆盖的SM足迹。
英文摘要：
We present the second public data release (DR) of the VISTA EXtension to Auxiliary Surveys (VEXAS), where we classify objects into stars, galaxies and quasars based on an ensemble of machine learning algorithms. The aim of VEXAS is to build the widest multi-wavelength catalogue, providing reference magnitudes, colours and morphological information for a large number of scientific uses. We apply an ensemble of 32 different machine learning models, based on three different algorithms and on different magnitude sets, training samples and classification problems on the three VEXAS DR1 optical+infrared (IR) tables. The tables were created in DR1 cross-matching VISTA near-IR data with WISE far-IR data and with optical magnitudes from the Dark Energy Survey (VEXAS-DESW), the Sky Mapper Survey (VEXAS-SMW), and the PanSTARRS (VEXAS-PSW). We assemble a large table of spectroscopically confirmed objects (415 628 unique objects), based on the combination of 6 different spectroscopic surveys that we use for training. We develop feature imputation to classify also objects for which magnitudes in one or more bands are missing. We classify in total ~90 million objects in the Southern Hemisphere. Among these,~62.9M (~52.6M) are classified as 'high confidence' ('secure') stars, ~920k (~750k) as 'high confidence' ('secure') quasars and ~34.8M (~34.1M) as 'high confidence' ('secure') galaxies, with probabilities $p_{\rm class}\ge 0.7$ ($p_{\rm class}\ge 0.9$). The density of high-confidence extragalactic objects varies strongly with the survey depth: at $p_{\rm class}\ge 0.7$, there are 111/deg$^2$ quasars in the VEXAS-DESW footprint and 103/deg$^2$ in the VEXAS-PSW footprint, while only 10.7/deg$^2$ in the VEXAS-SM footprint. Improved depth in the midIR and coverage in the optical and nearIR are needed for the SM footprint that is not already covered by DESW and PSW.
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