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

Elahesadat Naghib, Peter Yoachim, Robert J. Vanderbei, Andrew J. Connolly, R. Lynne Jones

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


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.

Original languageEnglish (US)
Article number151
JournalAstronomical Journal
Issue number4
StatePublished - Apr 2019

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • instrumentation: miscellaneous
  • surveys
  • telescope


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