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arXiv 1706.09397astro-ph.EP
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与大型综合巡天望远镜连接的近地天体轨道

Near-Earth Object Orbit Linking with the Large Synoptic Survey Telescope

Peter Vereš, Steven R. Chesley

摘要:

我们对LSST将近地和主带小行星探测与轨道联系起来的能力进行了详细的模拟。该研究的关键要素是高保真检测模型和以统计噪声和差异图像伪影的形式存在的错误检测。我们采用了移动对象处理系统(MOPS),以产生一个现实的检测密度的一个月的LSST调查的轨迹,轨道和轨道。这项研究的主要目的是了解:(a)近地天体与轨道的连接是否能够成功地进行实际测量;(b)假轨道和假轨道的数量是否可以管理;(c)连接轨道的准确性是否足以对发现和归属进行自动化处理。我们发现,小行星的整体密度是超过5000每个LSST领域附近的黄道上的反对派,加上高达3000个错误的检测,每个领域的良好看到。我们实现了93.6%的近地天体连接效率为H<22的轨道组成的tracklets从至少三个不同的夜晚在12天的间隔。衍生的近地天体目录由96%的正确链接组成。只有不到0.1%的轨道出现了错误的探测,其余的错误联系是由于主带混淆造成的,这是模拟时间跨度很短的人为因素。MOPS链接效率可以通过将检测结果精确地归因于已知对象以及通过改进内部kd树链接算法的调整来提高。

英文摘要:

We have conducted a detailed simulation of LSST's ability to link near-Earth and main belt asteroid detections into orbits. The key elements of the study were a high-fidelity detection model and the presence of false detections in the form of both statistical noise and difference image artifacts. We employed the Moving Object Processing System (MOPS) to generate tracklets, tracks and orbits with a realistic detection density for one month of the LSST survey. The main goals of the study were to understand whether a) the linking of Near-Earth Objects (NEOs) into orbits can succeed in a realistic survey, b) the number of false tracks and orbits will be manageable, and c) the accuracy of linked orbits would be sufficient for automated processing of discoveries and attributions. We found that the overall density of asteroids was more than 5000 per LSST field near opposition on the ecliptic, plus up to 3000 false detections per field in good seeing. We achieved 93.6% NEO linking efficiency for H<22 on tracks composed of tracklets from at least three distinct nights within a 12-day interval. The derived NEO catalog was comprised of 96% correct linkages. Less than 0.1% of orbits included false detections, and the remainder of false linkages stemmed from main belt confusion, which was an artifact of the short time span of the simulation. The MOPS linking efficiency can be improved by refined attribution of detections to known objects and by improved tuning of the internal kd-tree linking algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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