Ariel mission planning. Scheduling the survey of a thousand exoplanets
J.C. Morales, N. Nakhjiri, J. Colomé, I. Ribas, E. García, D. Moreno, F. Vilardell
Automatic scheduling techniques are becoming a crucial tool for the efficient planning of large astronomical surveys. A specific scheduling method is being designed and developed for the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (Ariel) mission planning based on a hybrid meta-heuristic algorithm with global optimization capability to ensure obtaining satisfying results fulfilling all mission constraints. We used this method to simulate the Ariel mission plan, to assess the feasibility of its scientific goals, and to study the outcome of different science scenarios. We conclude that Ariel will be able to fulfill the scientific objectives, i.e. characterizing ~1000 exoplanet atmospheres, with a total exposure time representing about 75-80% of the mission lifetime. We demonstrate that it is possible to include phase curve observations for a sample of targets or to increase the number of studied exoplanets within the mission lifetime. Finally, around 12-15% of the time can still be used for non-time constrained observations.
Comments: 23 pages, 8 figures, accepted for publication in Experimental Astronomy
Subjects: Instrumentation and Methods for Astrophysics (astro-ph.IM); Earth and Planetary Astrophysics (astro-ph.EP); Solar and Stellar Astrophysics (astro-ph.SR)
Cite as: arXiv:2201.07491 [astro-ph.IM] (or arXiv:2201.07491v1 [astro-ph.IM] for this version)
Submission history
From: Juan Carlos Morales
[v1] Wed, 19 Jan 2022 09:26:49 UTC (574 KB)
