Characterizing Earth Analogs in Reflected Light: Atmospheric Retrieval Studies for Future Space Telescopes
Y. Katherina Feng, Tyler D. Robinson, Jonathan J. Fortney, Roxana E., Lupu, Mark S. Marley, Nikole K. Lewis, Bruce Macintosh, Michael R. Line

TL;DR
This study develops an inverse modeling framework to evaluate the atmospheric characterization capabilities of future space telescopes for Earth-like exoplanets, focusing on the impact of spectral resolution and signal-to-noise ratio.
Contribution
It introduces a comprehensive retrieval method combining atmospheric models and noise simulations to assess detection limits for key gases in reflected light spectra.
Findings
Higher spectral resolution and SNR improve detection of atmospheric gases.
Weak detections are possible at R=70/SNR=15 and R=140/SNR=10.
Meaningful constraints require R=140 and SNR=20 data.
Abstract
Space-based high contrast imaging mission concepts for studying rocky exoplanets in reflected light are currently under community study. We develop an inverse modeling framework to estimate the science return of such missions given different instrument design considerations. By combining an exoplanet albedo model, an instrument noise model, and an ensemble Markov chain Monte Carlo sampler, we explore retrievals of atmospheric and planetary properties for Earth twins as a function of signal-to-noise ratio (SNR) and resolution (). Our forward model includes Rayleigh scattering, single-layer water clouds with patchy coverage, and pressure-dependent absorption due to water vapor, oxygen, and ozone. We simulate data at and from 0.4-1.0 m with SNR at 550 nm (i.e., for HabEx/LUVOIR-type instruments). At these same SNR, we simulate data for WFIRST…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Calibration and Measurement Techniques · Atmospheric Ozone and Climate
