论文标题
使用卷积神经网络的M83星系中的星形簇的研究
Study of star clusters in the M83 galaxy with a convolutional neural network
论文作者
论文摘要
我们介绍了螺旋星系M83中星团候选物的进化和结构参数的研究。为此，我们使用了在模拟群集中训练的卷积神经网络，能够快速识别和定位星团，以及从多波段图像中推断其参数。我们使用此管道在哈勃太空望远镜观测中检测3,380个群集候选。候选聚类的样本显示了整个银河系螺旋臂的年龄梯度，这与对密度波理论和其他研究的预测非常吻合。从螺旋臂的防尘车道中测得的那样，年轻的候选者人口在$ \ sim $ 0.4 kpc的距离上达到高峰，而较老的候选人则更加分散，但转向$ \ gtrsim $ \ gtrsim $ 0.7 kpc，在螺旋臂的主要部分。我们发现，位于螺旋臂的尾部，靠近尘埃车道的落后部分。我们还发现了银河中心附近的大量较旧的群集，并且远离中心的典型集群大小略有增加。
We present a study of evolutionary and structural parameters of star cluster candidates in the spiral galaxy M83. For this we use a convolutional neural network trained on mock clusters and capable of fast identification and localization of star clusters, as well as inference of their parameters from multi-band images. We use this pipeline to detect 3,380 cluster candidates in Hubble Space Telescope observations. The sample of cluster candidates shows an age gradient across the galaxy's spiral arms, which is in good agreement with predictions of the density wave theory and other studies. As measured from the dust lanes of the spiral arms, the younger population of cluster candidates peaks at the distance of $\sim$0.4 kpc while the older candidates are more dispersed, but shifted towards $\gtrsim$0.7 kpc in the leading part of the spiral arms. We find high extinction cluster candidates positioned in the trailing part of the spiral arms, close to the dust lanes. We also find a large number of dense older clusters near the center of the galaxy and a slight increase of the typical cluster size further from the center.
