Harnessing the Hubble Space Telescope Archives: A Catalog of 21,926 Interacting Galaxies
Harnessing the Hubble Space Telescope Archives: A Catalog of 21,926 Interacting Galaxies
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DOI：
10.3847/1538-4357/acc0ff
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发表时间：
2023-03
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影响因子：
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通讯作者：
David O’Ryan;B. Merín;B. Simmons;Ant'onia Vojtekov'a;Anna Anku;Mike Walmsley;I. Garland;T. Géron
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作者：
David O’Ryan;B. Merín;B. Simmons;Ant'onia Vojtekov'a;Anna Anku;Mike Walmsley;I. Garland;T. Géron
合并在星系的形成和演化中扮演着复杂的角色。继续提高我们对这些系统的理解需要更大的样本，这可能很难（甚至不可能）从单独的调查中选择。我们使用新的平台ESA数据实验室从哈勃太空望远镜科学档案中收集相互作用星系的目录;这个目录比以前公布的目录大了近一个数量级。特别是，我们将Zoobot卷积神经网络直接应用于HST F814 W图像的整个公共档案，并对哈勃源目录中的1.26亿个源进行概率交互预测。我们采用自动视觉表示和视觉分析相结合的方法来识别21，926个相互作用的星系系统的干净样本，其中大部分z < 1。这些系统中有65%在NASA河外星系数据库或Simbad中没有任何参考。在去除污染的过程中，我们还发现了许多其他感兴趣的物体，如引力透镜，边缘上的原行星盘和“背光”重叠星系。我们简要地调查了这个样本的基本属性，我们公开了我们的目录供社区使用。除了提供HST成像的科学有趣物体的新目录外，这项工作还展示了ESA Datalabs工具的强大功能，可以促进大量档案分析，而不会给最终用户带来很高的计算或存储负担。
Mergers play a complex role in galaxy formation and evolution. Continuing to improve our understanding of these systems requires ever larger samples, which can be difficult (even impossible) to select from individual surveys. We use the new platform ESA Datalabs to assemble a catalog of interacting galaxies from the Hubble Space Telescope science archives; this catalog is larger than previously published catalogs by nearly an order of magnitude. In particular, we apply the Zoobot convolutional neural network directly to the entire public archive of HST F814W images and make probabilistic interaction predictions for 126 million sources from the Hubble Source Catalog. We employ a combination of automated visual representation and visual analysis to identify a clean sample of 21,926 interacting galaxy systems, mostly with z < 1. Sixty-five percent of these systems have no previous references in either the NASA Extragalactic Database or Simbad. In the process of removing contamination, we also discover many other objects of interest, such as gravitational lenses, edge-on protoplanetary disks, and “backlit” overlapping galaxies. We briefly investigate the basic properties of this sample, and we make our catalog publicly available for use by the community. In addition to providing a new catalog of scientifically interesting objects imaged by HST, this work also demonstrates the power of the ESA Datalabs tool to facilitate substantial archival analysis without placing a high computational or storage burden on the end user.