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Pandora is an upcoming NASA SmallSat mission that will observe transitingexoplanets to study their atmospheres and the variability of their host stars.Efficient mission planning is critical for maximizing the science achieved withthe year-long primary mission. To this end, we have developed a scheduler basedon a metaheuristic algorithm that is focused on tackling the unique challengesof time-constrained observing missions, like Pandora. Our scheduling algorithmcombines a minimum transit requirement metric, which ensures we meetobservational requirements, with a `quality' metric that considers threefactors to determine the scientific quality of each observation window aroundan exoplanet transit (defined as a visit). These three factors are: observingefficiency during a visit, the amount of the transit captured by the telescopeduring a visit, and how much of the transit captured is contaminated by acoincidental passing of the observatory through the South Atlantic Anomaly. Theimportance of each of these factors can be adjusted based on the needs orpreferences of the science team. Utilizing this schedule optimizer, we developand compare a few schedules with differing factor weights for the PandoraSmallSat mission, illustrating trade-offs that should be considered between thethree quality factors. We also find that under all scenarios probed, Pandorawill not only be able to achieve its observational requirements using theplanets on the notional target list but will do so with significant timeremaining for ancillary science.

Schedule optimization for transiting exoplanet observations with NASA's Pandora SmallSat mission