Maximizing the ExoEarth Candidate Yield from a Future Direct Imaging Mission

TL;DR

This paper introduces Altruistic Yield Optimization, a new method to maximize exoEarth candidate yield in future imaging missions, showing it can significantly improve yield estimates and adapt to mission parameters.

Contribution

The paper presents a novel optimization method that enhances yield estimation accuracy and adaptability for exoEarth imaging missions.

Findings

Yield most sensitive to telescope diameter

Weak dependence on exozodi level

Method increases yield by up to 100%

Abstract

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.