标题： 使用大视场小孔径望远镜的实时暂现源探测智能观测方法 显示英文标题

标题： Smart obervation method with wide field small aperture telescopes for real time transient detection

摘要： 宽视场小孔径望远镜（WFSATs）常用于快速巡天。由多个WFSAT组成的望远镜阵列每晚能够多次扫描天空。它们会获取大量的数据，这些数据需要立即处理。本文提出了一种名为ARGUS（统一望远镜的天文目标检测框架）的实时凌星探测系统。ARGUS利用基于深度学习的天文探测算法，该算法在每个WFSAT的嵌入式设备中实现，以检测天文目标。检测到的目标位置和概率会被发送到经过训练的集成学习算法，以输出天体源的信息。在将这些源与星表匹配后，ARGUS将直接输出暂现候选体的类型和位置。我们使用模拟数据测试了ARGUS的性能，发现ARGUS可以稳健地提高WFSATs在暂现探测任务中的性能。 显示英文摘要

摘要： Wide field small aperture telescopes (WFSATs) are commonly used for fast sky survey. Telescope arrays composed by several WFSATs are capable to scan sky several times per night. Huge amount of data would be obtained by them and these data need to be processed immediately. In this paper, we propose ARGUS (Astronomical taRGets detection framework for Unified telescopes) for real-time transit detection. The ARGUS uses a deep learning based astronomical detection algorithm implemented in embedded devices in each WFSATs to detect astronomical targets. The position and probability of a detection being an astronomical targets will be sent to a trained ensemble learning algorithm to output information of celestial sources. After matching these sources with star catalog, ARGUS will directly output type and positions of transient candidates. We use simulated data to test the performance of ARGUS and find that ARGUS can increase the performance of WFSATs in transient detection tasks robustly.