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Detecting H₂O in exoplanet atmospheres is the first step on the path to determining planet habitability. Coronagraphic design currently limits the observing strategy used to detect H₂O, requiring the choice of specific bandpasses to optimize abundance constraints. In order to examine the optimal observing strategy for initial characterization of habitable planets using coronagraph-based direct imaging, we quantify the detectability of H₂O as a function of signal-to-noise ratio (S/N) and molecular abundance across 25 bandpasses in the visible wavelength range (0.5–1μm). We use a preconstructed grid consisting of 1.4 million geometric albedo spectra across a range of abundance and pressure, and interpolate to produce forward models for an efficient nested sampling routine, PSGnest. We first test the detectability of H₂O in atmospheres that mimic a modern-Earth twin, and then expand to examine a wider range of H₂O abundances; for each abundance value, we constrain the optimal 20% bandpasses based on the effective S/N of the data. We present our findings of H₂O detectability as functions of S/N, wavelength, and abundance, and discuss how to use these results for optimizing future coronographic instrument design. We find that there are specific points in wavelength where H₂O can be detected down to 0.74μmmore »with moderate-S/N data for abundances at the upper end of Earth’s presumed historical values, while at 0.9μm, detectability is possible with low-S/N data at modern Earth abundances of H₂O.

Precise radial velocity (PRV) surveys are important for the search for Earth analogs around nearby bright stars, which induce a small stellar reflex motion with an RV amplitude of ∼10 cm s⁻¹. Detecting such a small RV signal poses challenges to instrumentation, data analysis, and the precision of astrophysical models to mitigate stellar jitter. In this work, we investigate an important component in the PRV error budget—the spectral contamination from the Earth’s atmosphere (tellurics). We characterize the effects of telluric absorption on the RV precision and quantify its contribution to the RV error budget over time and across a wavelength range of 350 nm–2.5μm. We use simulated solar spectra with telluric contamination injected, and we extract the RVs using two commonly adopted algorithms: dividing out a telluric model before performing cross-correlation or forward modeling the observed spectrum incorporating a telluric model. We assume various degrees of cleanness in removing the tellurics. We conclude that the RV errors caused by telluric absorption can be suppressed to close to or even below 1–10 cm s⁻¹in the blue optical region. At red through near-infrared wavelengths, however, the residuals of tellurics can induce an RV error on the meter-per-second level even under themore »most favorable assumptions for telluric removal, leading to significant systematic noise in the RV time series and periodograms. If the red-optical or near-infrared becomes critical in the mitigation of stellar activity, systematic errors from tellurics can be eliminated with a space mission such as EarthFinder.