A Framework for Telescope Schedulers: With Applications to the Large Synoptic Survey Telescope

Abstract

© 2019. The American Astronomical Society. All rights reserved. How ground-based telescopes schedule their observations in response to different variables can significantly impact their efficiency. Namely, competing science priorities and constraints, variations in the weather, and the visibility of a particular part of the sky are some of the determining variables. In this paper we introduce the Feature-based telescope scheduler, which is an automated, decision-making algorithm. It offers controllability of the behavior, adjustability of the mission, and quick recoverability from interruptions for large ground-based telescopes. By framing the Feature-based telescope scheduler in the context of a coherent mathematical model, the functionality and performance of the algorithm are simple to interpret. Consequently, adapting this scheduler for a broad range of ground-based instruments is straightforward. This paper presents a generic version of the Feature-based scheduler, with minimal manual tailoring. We demonstrate its potential and flexibility to serve as a foundation for schedulers of the ground-based instruments. In addition, a modified version of the Feature-based scheduler for the Large Synoptic Survey Telescope (LSST) is introduced and compared to the previous LSST schedulers.