Faster Exo-Earth Yield for HabEx and LUVOIR via Extreme Precision Radial Velocity Prior Knowledge
The HabEx and LUVOIR mission concepts reported science yields for mission scenarios in which the instruments must search for potentially habitable planets, determine their orbits, and, if worthwhile, invest the integration time for a spectral characterization. We evaluate the impact of prior knowledge of planet existence and orbital parameters on yield for four mission concept architectures: HabEx 4m telescope with hybrid starshade and coronagraph, HabEx4m telescope with starshade only, HabEx 4m telescope with coronagraph only, and LUVOIR B8m telescope with coronagraph only. We use perfect prior knowledge to establish an upperbound on yield and use partial prior knowledge from a potential future extreme precision radial velocity (EPRV) instrument with3cm∕ssensitivity. We detail a modeling framework that per-forms dynamically responsive observation scheduling with realistic mission constraints. We evaluate exo-Earth yields against three metrics of spectral characterization for the four mission architectures and three levels of prior knowledge (none, partial, and perfect). The EPRV pro-vided prior knowledge increases yields by∼30%and accelerates by a factor of 3 to 6 the time to achieve half of the yield of the mission. Prior knowledge makes all the mission architectures more nimble and powerful, and most especially starshade-based architectures. With prior knowledge, a small telescope with a starshade can achieve comparable yield to a larger telescope with a coronagraph.