ALTSched: Improved Scheduling for Time-Domain Science with LSST

Abstract

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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Cited by in corpus (4)

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• Observing the earliest moments of supernovae using strong gravitational lenses
• Optimising LSST Observing Strategy for Weak Lensing Systematics