MAXIMIZING THE ExoEarth CANDIDATE YIELD FROM A FUTURE DIRECT IMAGING MISSION
By C. Stark, A. Roberge, A. Mandell, T. Robinson. 2014
146 citations recorded by the source corpus.
ExoEarth yield is a critical science metric for future exoplanet imaging missions. Here we estimate exoEarth candidate yield using single visit completeness for a variety of mission design and astrophysical parameters. We review the methods used in previous yield calculations and show that the method choice can significantly impact yield estimates as well as how the yield responds to mission parameters. We introduce a method, called Altruistic Yield Optimization, that optimizes the target list and exposure times to maximize mission yield, adapts maximally to changes in mission parameters, and increases exoEarth candidate yield by up to 100% compared to previous methods. We use Altruistic Yield Optimization to estimate exoEarth candidate yield for a large suite of mission and astrophysical parameters using single visit completeness. We find that exoEarth candidate yield is most sensitive to telescope diameter, followed by coronagraph inner working angle, followed by coronagraph contrast, and finally coronagraph contrast noise floor. We find a surprisingly weak dependence of exoEarth candidate yield on exozodi level. Additionally, we provide a quantitative approach to defining a yield goal for future exoEarth-imaging missions.
Subfields: Astronomy and Astrophysics
View Paper: https://www.semanticscholar.org/paper/b6acc779a1ba6f8ab36dc5640088ff02fb6615f7
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In Astronomy and Astrophysics
- E. Wolf
- T. Robinson
- V. Meadows
- D. Deming
- E. Schwieterman
- Giada N. Arney
- S. Domagal‐Goldman
- J. Grenfell
Citations in the corpus
- Pale Orange Dots: The Impact of Organic Haze on the Habitability and Detectability of Earthlike Exoplanets (2016, background): “G and K dwarf planets, on the other hand, may have organic haze, and such stars will be important targets for future direct imaging missions (Stark et al. 2014).”
- Exoplanet Biosignatures: A Review of Remotely Detectable Signs of Life (2017, background): “This lesson from Earth history should be kept in mind when creating statistical frameworks for the prevalence of life given negative results and when estimating biosignature yields for surveys of candidate exoEarths (Stark et al., 2014, 2016; Léger et al., 2015).”