Presentation #102.44 in the session Poster Session.
Characterizing the masses and orbits of near-Earth-mass planets is crucial for interpreting observations from future direct imaging missions (e.g., LuvEx). Newman et al. (2022) simulated several 10-year extreme-precision radial velocity (RV) surveys with differing telescope architectures, demonstrating that they can precisely measure the masses of potentially habitable Earth-mass planets in the absence of stellar variability. Here, we introduce Gaussian process kernels for active regions, granulation, and oscillations to investigate the effect of stellar variability on the signal-to-noise ratio (SNR) of the planet mass measurements in these simulated surveys. We present the impact of these components of stellar variability by exploring both their combined and individual effect on each survey architecture, in addition to modified architectures where we vary the survey duration and instrumental precision. We find that correlated noise due to active regions has the largest effect on the observed mass SNR, followed by granulation, with p-mode oscillations having little impact on the proposed survey strategies. In the presence of correlated noise, 5-cm s–1 instrumental precision offers little improvement over 10-cm s–1 precision, highlighting the need to mitigate astrophysical variability. Finally, with our noise models, reaching 10% mass precision on Earth-analogs in the simulated 10-year surveys is only possible for planets orbiting stars < 0.76 M⊙ (< 0.86 M⊙ for a 15-year survey); reaching this precision threshold for planets orbiting solar mass stars will require additional observations per target than simulated or improved mitigation of astrophysical variability.