The Asteroid Terrestrial-impact Last Alert System (ATLAS) observes the visible sky every night in search of dangerous asteroids. With four (soon five) sites ATLAS is facing new challenges for scheduling observations and linking detections to identify moving asteroids. Flexibility in coping with diverse observation sites and times of detections that can be linked is critical, as is optimization of observing time for coverage versus depth. We present new algorithms to fit orbits rapidly to sky-plane observations, and to test and link sets of detections to find the ones which belong to moving objects. The PUMA algorithm for fitting orbits to angular positions on the sky executes in about a millisecond, orders of magnitude faster than the methods currently in use by the community, without sacrifice in accuracy. The PUMA software should be generally useful to anyone who needs to test many sets of detections for consistency with a real orbit. The PUMALINK algorithm to find linkages among sets of detections has similarities to other approaches, notably HelioLinC, but it functions well at asteroid ranges of a small fraction of an astronomical unit. PUMALINK is fast enough to test 10 million possible tracklets against one another in a half hour of computer time. Candidate linkages are checked by the PUMA library to test that the detections correspond to a real orbit, even at close range, and the false alarm rate is manageable. Sky surveys that produce large numbers of detections from large numbers of exposures may find the PUMALINK software helpful. We present the results of tests of PUMALINK on three data sets which illustrate PUMALINK’s effectiveness and economy: 2 weeks of all ATLAS detections over the sky, 2 weeks of special ATLAS opposition observations with long exposure time, and 2 weeks of simulated LSST asteroid observations. Detection probabilities of linkages must be traded against false alarm rate, but a representative choice for PUMALINK might be 90% detection probability for real objects while keeping the false alarm rate below 10% for a 100:1 population of false:real. Although optimization of the tradeoffs between detection probability, execution time, and false alarm rate is application specific and beyond the scope of this paper, we provide guidance on methods to distinguish false alarms from correct linkages of real objects.

中文翻译：

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连接运动物体的天空平面观测


小行星撞击地球最后警报系统（ATLAS）每天晚上都会观察可见的天空，寻找危险的小行星。 ATLAS 拥有四个（很快将有五个）站点，在安排观测和连接探测以识别移动小行星方面面临着新的挑战。灵活应对不同的观测地点和可关联的检测时间至关重要，覆盖范围与深度的观测时间优化也至关重要。我们提出了新的算法，可以快速将轨道与天空平面观测相匹配，并测试和链接检测集以找到属于移动物体的检测。用于将轨道拟合到天空上的角位置的 PUMA 算法的执行时间约为一毫秒，比社区当前使用的方法快几个数量级，而且不会牺牲准确性。 PUMA 软件对于需要测试多组检测以确保与真实轨道的一致性的任何人来说通常都是有用的。用于查找检测集之间联系的 PUMALINK 算法与其他方法（尤其是 HelioLinC）有相似之处，但它在天文单位一小部分的小行星范围内运行良好。 PUMALINK 的速度足够快，可以在半小时的计算机时间内测试 1000 万个可能的轨迹。 PUMA 库会检查候选链接，以测试检测是否对应于真实轨道，即使是在近距离，并且误报率是可控的。通过大量曝光产生大量检测结果的天空观测可能会发现 PUMALINK 软件很有帮助。 我们展示了 PUMALINK 在三个数据集上的测试结果，说明了 PUMALINK 的有效性和经济性：2 周的所有 ATLAS 天空探测、2 周的长曝光时间特殊 ATLAS 对冲观测以及 2 周的模拟 LSST 小行星观测。链接的检测概率必须与误报率进行权衡，但 PUMALINK 的代表性选择可能是真实对象的 90% 检测概率，同时将误报率保持在 10% 以下（假：真实比例为 100:1）。尽管检测概率、执行时间和误报率之间的权衡优化是特定于应用的并且超出了本文的范围，但我们提供了区分误报与真实对象的正确链接的方法的指导。