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Title: Maximizing the ExoEarth candidate yield from a future direct imaging mission

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.
Authors:
 [1] ; ;  [2] ;  [3]
  1. NASA Goddard Space Flight Center, Exoplanets and Stellar Astrophysics Laboratory, Code 667, Greenbelt, MD 20771 (United States)
  2. NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)
  3. NASA Ames Research Center, Moffett Field, CA 94035 (United States)
Publication Date:
OSTI Identifier:
22370025
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astrophysical Journal; Journal Volume: 795; Journal Issue: 2; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ASTROPHYSICS; COMPARATIVE EVALUATIONS; DESIGN; NOISE; OPTIMIZATION; PLANETS; TELESCOPES