Simulations for Planning Next-Generation Exoplanet Radial Velocity Surveys Patrick D Newman1, Peter Plavchan1, Jennifer A. Burt2, Johanna Teske3, Eric E. Mamaje2, Stephanie Leifer4, B. Scott Gaudi5, Garry Blackwood2, Rhonda Morgan2 1George Mason University, 2Jet Propulsion Laboratory, 3Carnegie Institution for Science, 4The Aerospace Corporation, 5The Ohio State University Abstract Future direct imaging missions such as HabEx and LUVOIR aim to catalog and characterize Earth-mass analogs around nearby stars. The exoplanet yield of these missions will be dependent on the frequency of Earth-like planets, and potentially the a priori knowledge of which stars speciﬁcally host suitable planetary systems. Ground or space based radial velocity surveys can potentially perform the pre-selection of targets and assist in the optimization of observation times, as opposed to an uninformed direct imaging survey. In this paper, we present our framework for simulating future radial velocity surveys of nearby stars in support of direct imaging missions. We generate lists of exposure times, observation time-series, and radial velocity time-series given a direct imaging target list. We generate simulated surveys for a proposed set of telescopes and precise radial velocity spectrographs spanning a set of plausible global-network architectures that may be considered for next generation extremely precise radial velocity surveys. We also develop ﬁgures of merit for observation frequency and planet detection sensitivity, and compare these across architectures. From these, we draw conclusions, given our stated assumptions and caveats, to optimize the yield of future radial velocity surveys in support of direct imaging missions. We ﬁnd that all of our considered surveys obtain suﬃcient numbers of precise observations to meet the minimum theoretical white noise detection sensitivity for Earth-mass habitable zone planets, with margin to explore systematic eﬀects due to stellar activity and correlated noise. Survey Targets, Goals, and Architectures 50 100 150 200 250 300 350 Day of Year 0.0 0.2 0.4 0.6 0.8 1.0 Fraction of Clear Nights Site Weather Mauna Kea Kitt Peak Calar Alto Las Campanas Sutherland Siding Spring Figure: Left: General diagrams of diﬀerent architecture(telescope/spectrograph combinations). Right: Nightly weather (as fraction of useable nights) at the sites considered for these surveys. We took a list of 101 nearby (≤15 pc) FGK stars that are considered both good direct imaging and RV targets, and split them into two mostly non-overlaping groups (51 north and 58 south). We performed simulated 10 year surveys on them across seven diﬀerent architectures (telescope/instrument combinations) on six diﬀerent sites (3 north, 3 south). Architecture I IIa IIb V Telescopes 6x2.4 m 2x6 m and 4x4 m 6x4 m 6x3 m Collecting area by aperture 2.4 m = 4.2 m2 4 m = 9.5 m2; 6 m = 27 m2 4 m = 9.5 m2 3 m = 6.3 m2 Time allocation 100% 100% 100% 100% Wavelength coverage 380-930 nm 380 - 930 nm 380 - 930 nm 500-1700 nm Spectral resolution 180 000 180 000 180 000 180 000 Total system eﬃciency 6% 6% 6% 7% instrument noise ﬂoor 10 cm/s 5 cm/s 5 cm/s 10 cm/s Required (peak) SNR/pix 300 300 300 300 Required RV precision 10 cm/s 10 cm/s 10 cm/s 10 cm/s Observation cadence per star 1 / night 3 / night 3 / night 2 / telescope / night Architecture VI VIIIa VIIIb Telescopes 6x arrays of 1 m 2x10 m and 4x 3.5 m 2x10 m and 6x2.4 m Collecting area by aperture 0.61m2 each; array is 9.5 m2 10 m = 75 m2; 3.5 m = 9.5 m2 10 m = 75 m2; 2.4 m = 4.2 m2 Time allocation 100% 25% of 10 m; 100% of 3.5m 25% of 10 m; 100% of 2.4 m Wavelength coverage 500-800 nm 380-930 nm 380-930 nm Spectral resolution 150 000 180 000 180 000 Total system eﬃciency 6% 6% 6% instrument noise ﬂoor 10 cm/s 5 cm/s 5cm/s Required (peak) SNR/pix 300 1000 for the 10 m; 300 for 3.5 m 1000 for the 10 m; 300 for 2.4 m Required RV precision 10 cm/s 15 cm/s on 3.5 m; 5 cm/s on 10 m 15 cm/s on 2.4 m; 5 cm/s on 10 m Obser