NASA's Pandora SmallSat Mission: Simulated Modeling and Retrieval of Near-Infrared Exoplanet Transmission Spectra

Abstract

Pandora is a SmallSat mission dedicated to understanding exoplanets and their host stars by disentangling the impact of stellar heterogeneity on exoplanet transmission spectra. Selected as a NASA Astrophysics Pioneers mission in 2021, Pandora will provide simultaneous long-term visible photometric monitoring (0.4--0.7 $μ$m) and low-resolution near-infrared (NIR) spectroscopy (0.9--1.6 $μ$m) of transiting systems for the purposes of monitoring host star variability and characterizing exoplanetary atmospheres. Pandora's year-long prime mission from 2026 to 2027 coincides with the middle of a decade defined by targeted efforts for atmospheric characterization of exoplanets, offering a key opportunity to leverage this new resource to maximize science with JWST and other observatories. Here we investigate Pandora's anticipated performance for the general exoplanet population accessible to transit spectroscopy, from hot Jupiters to temperate sub-Neptunes. By modeling the atmospheres of five test cases broadly consistent with the bulk properties of HD~209458~b, HD~189733~b, WASP-80~b, HAT-P-18~b, and K2-18~b, we find that Pandora may provide abundance constraints as precise as $\sim$1.0\,dex for main atmospheric absorbers such as H$_2$O and CH$_4$. Then, we explore the synergies between Pandora and JWST. Our results suggest that targets with JWST data in the near-infrared can benefit from the addition of Pandora observations and result in more reliable abundance estimates than with JWST data alone. Moreover, Pandora can serve the community by providing precursory observations of targets of interest for JWST atmospheric characterization. We conclude by outlining strategies for the use of Pandora as a standalone observatory and in synergy with JWST.

Figures (13)

• Figure 1: The absorption cross sections of common absorbers in exoplanet atmospheres considered in this work, shown at a pressure and temperature of 0.1 mbar and 1000 K. The wavelength coverage of Pandora's NIR detector (NIRDA), JWST's NIRCam F322W2 and F444W filters, and HST's WFC3 instrument (for the G141 grism) are shown. Pandora/NIRDA covers absorption bands of H$_2$O, CH$_4$, NH$_3$ and the wing of the K doublet, making it most sensitive to these absorbers.
• Figure 2: The range of uncertainties predicted by our calculations for Pandora observations of a warm Jupiter-like system (here, WASP-80 b) with varying stellar magnitude, after binning to $R\simeq30$. Different stellar fluxes and detector properties at different wavelengths will lead to different uncertainties throughout the bandpass; the bands here represent the range between the lowest and highest uncertainties. Stacking multiple observations will provide lower uncertainties, particularly for fainter targets. The inset shows the uncertainties for brighter stars, for which Pandora can achieve precisions as low as $\sim$30 ppm when multiple transits are observed. The magnitudes of stars included in the Pandora primary target list are shown as diamonds.
• Figure 3: Synthetic forward models and observations with Pandora's NIRDA instrument of the five targets. The data is binned to a resolution of $R\simeq30$, and error bars are simulated for ten transit observations. The 1.4 $\mu$m water absorption band is highlighted for reference, though K2-18 b shows a similar feature from CH$_4$ absorption.
• Figure 4: H$_2$O posterior distributions for our five targets. The green distributions show the retrieved posteriors from the simple model, and the blue represents the comprehensive model, which includes clouds and hazes (both described in Section \ref{['sec:fwd_model']}). Maroon lines indicate the injected true values from Table \ref{['table:params_priors']} in Appendix \ref{['appendix:priors_and_model']}, and the error bars represent the 16th to 84th percentile range. While the simple model is able to accurately retrieve the H$_2$O abundance with high precision, the inclusion of clouds and hazes leads to degeneracies with the H$_2$O abundance benneke_how_2013welbanks_degeneracies_2019, making it more difficult to constrain H$_2$O with the realistic model.
• Figure 5: Top: The synthetic spectrum of K2-18 b overlaid with forward models with varying scattering slope enhancement amplitudes. Higher enhancement amplitudes affect the observed spectra further into the NIR, muting feature sizes in the $\sim$1.0 $\mu$m range. Bottom: The 68% confidence interval of the posteriors of the enhancement ($\log(a)$; purple) and slope ($\gamma$; orange) for the different enhancements considered. At enhancements $\gtrsim10^6$, the scattering slope more strongly affects the Pandora bandpass, allowing for more precise constraints on both parameters.