论文标题
Fink，为LSST社区的新一代经纪人
Fink, a new generation of broker for the LSST community
论文作者
论文摘要
Fink是一位经纪人，旨在通过大型时域警报流启用科学，例如即将到来的Vera C. Rubin C. Rubin Observatory时空遗产（LSST）。它展示了传统的天文经纪人特征，例如自动摄入，注释，选择和重新分配有希望的瞬态科学警报。它还旨在通过提供实时瞬态分类来超越传统经纪人的功能，该分类通过使用最新的深度学习和自适应学习技术不断改进。这些不断发展的附加值将使不同科学案例的LSST光度数据获得更准确的科学输出，同时也导致新发现的较高发生率将伴随调查的演变。在本文中，我们介绍了Fink，其科学动机，建筑和当前状态，包括使用Zwicky Transient设施警报流的首次科学验证案例。
Fink is a broker designed to enable science with large time-domain alert streams such as the one from the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). It exhibits traditional astronomy broker features such as automatised ingestion, annotation, selection and redistribution of promising alerts for transient science. It is also designed to go beyond traditional broker features by providing real-time transient classification which is continuously improved by using state-of-the-art Deep Learning and Adaptive Learning techniques. These evolving added values will enable more accurate scientific output from LSST photometric data for diverse science cases while also leading to a higher incidence of new discoveries which shall accompany the evolution of the survey. In this paper we introduce Fink, its science motivation, architecture and current status including first science verification cases using the Zwicky Transient Facility alert stream.
