Optimal Architectures and Survey Designs for Maximizing the Yields of Direct-Imaging Exoplanet Missions

Christopher Stark , Giada N. Arney , Ruslan Belikov , Matthew R. Bolcar , Eric Cady , Brendan P. Crill , Shawn D. Domagal-Goldman , Shannon D. Dulz , B. Scott Gaudi , Tyler D. Groff , Brian A. Hicks , Ravi K. Kopparapu , John E. Krist , P. Douglas Lisman , Eric E. Mamajek , Avi M. Mandell , Dimitri Mawet , Johan Mazoyer , Michael W. Mcelwain , Bertrand Mennesson , Rhonda Morgan , Mamadou N'Diaye (1, 2, 3) , Peter Plavchan , Laurent Pueyo , Bernard J. Rauscher , A. J. Eldorado Riggs , Aki Roberge , Tyler D. Robinson , Garreth Ruane , Kathryn St. Laurent , Dan Sirbu , Remi Soummer , Dmitry Savransky , Stuart B. Shaklan , Karl R. Stapelfeldt , Neil T. Zimmerman

1 LAGRANGE - Joseph Louis LAGRANGE
2 CNRS - Centre National de la Recherche Scientifique
3 OCA - Observatoire de la Côte d'Azur

Our ability to answer scientific questions about exoplanets hinges on satisfying an age-old astronomical requirement: a sufficient sample size. Thus, the yield of exoplanets is critical to understanding the scientific impact of future missions. We discuss how the yield of directly-imaged exoplanets depends on mission scale and survey design.

Domaines: Planète et Univers [physics]; Physique [physics]

Christopher Stark, Giada N. Arney, Ruslan Belikov, Matthew R. Bolcar, Eric Cady, et al.. Optimal Architectures and Survey Designs for Maximizing the Yields of Direct-Imaging Exoplanet Missions. 2020. ⟨hal-03086408⟩