论文标题

用支持向量机搜索分子流出:Cygnus中的乌云复合物

Searching for Molecular Outflows with Support Vector Machines: Dark Cloud Complex in Cygnus

论文作者

Zhang, Shaobo, Yang, Ji, Xu, Ye, Chen, Xuepeng, Su, Yang, Sun, Yan, Zhou, Xin, Li, Yingjie, Lu, Dengrong

论文摘要

我们根据46.75 deg^2 CO的同位素学数据的图像卷轴卷绘画(MWISP)调查提出了一项对Cygnus区域乌云复合物的分子流出的调查。引入了一种监督的机器学习算法,支持向量机(SVM),以加速我们对12CO和13CO j = 1-0排放的数据立方中流出功能的视觉评估。总共确定了130个流出候选物,其中77个显示了双极结构,118个是新的检测。在空间上,这些流出位于密集的分子云内,其中一些位于簇中或延长的线性结构中,以追踪基础气体丝形态。沿着视线,97、31和2个候选人分别居住在当地,珀尔修斯和外臂。年轻的恒星物体是在大多数流出附近发现流出驱动程序,而36个候选人没有相关的来源。我们检测到的流出簇在其性质中是不均匀的。然而,我们表明流出不能在云尺度上注入湍流能量。取而代之的是,它们充其量仅限于影响所谓的“团块”和“核心”量表,并且仅在简短(〜0.3 Myr)估计的时间表上。结合文献中的流出样本,我们的工作显示出紧密的流出质量大小相关性。

We present a survey of molecular outflows across the dark cloud complex in the Cygnus region, based on 46.75 deg^2 field of CO isotopologues data from Milky Way Imaging Scroll Painting (MWISP) survey. A supervised machine learning algorithm, Support Vector Machine (SVM), is introduced to accelerate our visual assessment of outflow features in the data cube of 12CO and 13CO J = 1-0 emission. A total of 130 outflow candidates are identified, of which 77 show bipolar structures and 118 are new detections. Spatially, these outflows are located inside dense molecular clouds and some of them are found in clusters or in elongated linear structures tracing the underlying gas filament morphology. Along the line of sight, 97, 31, and 2 candidates reside in the Local, Perseus, and Outer arm, respectively. Young stellar objects as outflow drivers are found near most outflows, while 36 candidates show no associated source. The clusters of outflows that we detect are inhomogeneous in their properties; nevertheless, we show that the outflows cannot inject turbulent energy on cloud scales. Instead, at best, they are restricted to affecting the so called "clump" and "core" scales, and this only on short (~0.3 Myr) estimated timescales. Combined with outflow samples in the literature, our work shows a tight outflow mass-size correlation.

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