AAS2RTO: 从自动警报流到实时观测：为LSST时代的瞬变天体快速后续观测做准备
AAS2RTO: Automated Alert Streams to Real-Time Observations: Preparing for rapid follow-up of transient objects in the era of LSST
AI总结：
本研究推出Python工具AAS2RTO，采用贪心算法结合多维度得分排序瞬变观测候选目标，适配LSST时代海量瞬变源发现需求，已验证其在Ia型超新星后续观测优先级筛选中的有效性。
AI中文摘要：
即将开展的薇拉·C·鲁宾空间与时间遗产巡天（LSST）每晚将发现数万个天体物理瞬变源，远超现有光谱后续观测能力的承载上限。为后续观测精心筛选候选目标优先级，能让配备单天体光谱仪的小型望远镜实现最大科学回报。我们推出AAS2RTO，这是一款用Python编写的天体物理瞬变候选目标优先级排序工具。AAS2RTO具备灵活性，可实现任意数量考量瞬变源观测特性的筛选标准，同时还会考虑候选目标在指定观测站点的可见性。当新的瞬变数据发布时，AAS2RTO生成的优先级候选列表会持续更新，因此可应用于具备各类科学目标的观测项目。AAS2RTO采用贪心算法对候选目标排序，每个候选目标对应一个单一数值即“得分”。得分通过构建多个简单数值因子计算得出，每个因子分别考量候选目标适合后续观测的各方面竞争维度。目前AAS2RTO的配置主要适配兹威基瞬变设施（ZTF）的测光数据，这些数据由经认证的LSST社区代理分发。我们提供了一个应用示例：通过设定一套筛选标准，为接近亮度峰值的Ia型超新星（SNe Ia）观测排序，为使用丹麦1.54米望远镜光谱仪开展观测做准备。利用ZTF的历史警报样本，我们评估了所设计的筛选标准，以此估算1.5米望远镜可观测的Ia型超新星数量。最后，我们还评估了这套标准应用于Ia型超新星的模拟LSST观测数据时的性能。
英文摘要：
The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST) will discover tens of thousands of astrophysical transients per night, far outpacing available spectroscopic follow-up capabilities. Carefully prioritising candidates for follow-up observations will maximise the scientific return from small telescopes with a single-object spectrograph. We introduce AAS2RTO, an astrophysical transient candidate prioritisation tool written in Python. AAS2RTO is flexible in that any number of criteria that consider observed properties of transients can be implemented. The visibility of candidates from a given observing site is also considered. The prioritised list of candidates provided by AAS2RTO is continually updated when new transient data are made available. Therefore, it can be applied to observing campaigns with a wide variety of scientific motivations. AAS2RTO uses a greedy algorithm to prioritise candidates. Candidates are represented by a single numerical value, or `score'. Scores are computed by constructing simple numerical factors which individually consider the competing facets of a candidate which make it suitable for follow-up observation. AAS2RTO is currently configured to work primarily with photometric data from the Zwicky Transient Facility (ZTF), distributed by certified LSST community brokers. We provide an example of how AAS2RTO can be used by defining a set of criteria to prioritise observations of type Ia supernovae (SNe Ia) close to peak brightness, in preparation for observations with the spectrograph at the Danish-1.54m telescope. Using a sample of archival alerts from ZTF, we evaluate the criteria we have designed to estimate the number of SNe Ia that we will be able to observe with a 1.5m telescope. Finally, we evaluate the performance of our criteria when applied to mock LSST observations of SNe Ia.
