ALTSched：基于LSST的时域科学改进调度算法
ALTSched: Improved Scheduling for Time-Domain Science with LSST
摘要：
望远镜调度是为测量系统确定最佳观测序列（指向和滤波器选择）的任务。由于在所有可能的多年观测序列上进行优化在计算上是困难的，因此，决策者使用随机选择来选择给定时间的最佳观测。贪婪的调度程序通过选择最大化标量优值函数的观测值来选择下一个观测值，标量优值函数作为望远镜科学目标的代理。这种自下而上的调度方法不能保证产生一个所有观测值的价值之和最大化的调度。作为一种替代贪婪的调度器，我们引入ALTSched，它需要一个自上而下的方法来调度。ALTSched不是只考虑下一次观测，而是对天空的哪个区域和哪个滤波器进行全局决策，然后将这些决策细化为沿子午线进行的观测序列，以最大化SNR。我们实现ALTSched的大型综合巡天望远镜（LSST），并表明，它等于或优于基线贪婪调度基本上所有的定量性能指标。由于其简单性，我们的实现比OpSim（LSST项目目前使用的模拟贪婪调度器）快得多：可以在4分钟内模拟一个完整的十年调查，而OpSim则需要数十小时。LSST的硬件是固定的，因此改进调度算法是优化LSST性能的唯一方法之一。我们看到ALTSched作为一个原型调度器，它给出了LSST可实现的性能下限。
英文摘要：
Telescope scheduling is the task of determining the best sequence of observations (pointings and filter choices) for a survey system. Because it is computationally intractable to optimize over all possible multi-year sequences of observations, schedulers use heuristics to pick the best observation at a given time. A greedy scheduler selects the next observation by choosing whichever one maximizes a scalar merit function, which serves as a proxy for the scientific goals of the telescope. This sort of bottom-up approach for scheduling is not guaranteed to produce a schedule for which the sum of merit over all observations is maximized. As an alternative to greedy schedulers, we introduce ALTSched, which takes a top-down approach to scheduling. Instead of considering only the next observation, ALTSched makes global decisions about which area of sky and which filter to observe in, and then refines these decisions into a sequence of observations taken along the meridian to maximize SNR. We implement ALTSched for the Large Synoptic Survey Telescope (LSST), and show that it equals or outperforms the baseline greedy scheduler in essentially all quantitative performance metrics. Due to its simplicity, our implementation is considerably faster than OpSim, the simulated greedy scheduler currently used by the LSST Project: a full ten year survey can be simulated in 4 minutes, as opposed to tens of hours for OpSim. LSST's hardware is fixed, so improving the scheduling algorithm is one of the only remaining ways to optimize LSST's performance. We see ALTSched as a prototype scheduler that gives a lower bound on the performance achievable by LSST.
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