NASA's Pandora SmallSat Mission: Simulating the Impact of Stellar Photospheric Heterogeneity and Its Correction

Abstract

Stellar photospheric heterogeneity is a dominant astrophysical systematic impacting exoplanet transmission spectroscopy. NASA's Pandora SmallSat Mission is designed to address this challenge through contemporaneous visible photometry and NIR spectroscopy of exoplanet host stars. Here we present an end-to-end simulation study quantifying Pandora's ability to infer stellar photospheric properties and correct stellar contamination using out-of-transit observations. We construct eight representative stellar activity scenarios and generate 160 simulated Pandora datasets, incorporating time-dependent stellar spectra, instrument response, and noise. Given accurate models, Bayesian retrievals of Pandora spectrophotometry recover photospheric temperatures with typical uncertainties of ${\approx}30$ K, with no significant bias. Models with two spectral components (i.e., quiescent photosphere and spots) are strongly favored in 95% of cases; one-component models are preferred when true spot filling factors fall below a detection threshold of ${\approx}0.3$%. We propagate the true and inferred stellar parameters to compute true, inferred, and residual contamination signals under physically motivated spot geometries. For simple spot distributions, contamination signals of $10^2{-}10^3$ ppm are reduced to ${\lesssim}10$ ppm, well below Pandora's expected transmission spectroscopy precision (30$-$100 ppm). For more complex spot distributions, geometric degeneracies limit deterministic corrections, leaving residual contamination at the $10^3$ ppm level that must be mitigated using additional constraints, such as spot-crossing events and joint stellar-planetary retrievals of transmission spectra. These results define regimes in which stellar contamination can be corrected from stellar observations alone and show how Pandora stellar observations can identify cases where additional information is required.