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

Yoav Rotman, Peter McGill+23 more|arXiv (Cornell University)|Mar 4, 2026

Stellar, planetary, and galactic studies0 citations

TL;DR

The paper assesses Pandora’s capability to characterize exoplanet atmospheres and disentangle stellar contamination by simulating Pandora NIR spectroscopy (0.9–1.6 μm) paired with visible photometry, and explores joint Pandora–JWST retrievals across five benchmark planets.

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.

Motivation & Objective

• Motivate exoplanet atmospheric characterization via transmission spectroscopy and address stellar heterogeneity (TLS effect) on observed spectra.
• Evaluate Pandora's ability to constrain atmospheric composition, temperature, and metallicity for a set of benchmark exoplanets.
• Investigate the impact of combining Pandora data with JWST observations on retrieval accuracy and precision.
• Assess observational limits, multi-transit benefits, and the feasibility of detecting atmospheric features with Pandora.

Proposed method

• Simulate transmission spectra for five target exoplanets using the Aurora forward-model and transmission framework.
• Model Pandora NIRDA observations and JWST NIRCam data to create synthetic, multi-instrument datasets.
• Perform Bayesian atmospheric retrievals using MultiNest via PyMultiNest to infer abundances, temperature, and clouds/hazes.
• Compare simple (cloud- and haze-free) versus comprehensive (clouds/hazes included) atmospheric models to assess degeneracies.
• Evaluate Bayesian evidence for presence of specific absorbers (H2O, CH4, NH3) and quantify model preference via Bayes factors.

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 and HST’s WFC3 instrument (for the G141 grism) are shown. Pando

Experimental results

Research questions

• RQ1 How well can Pandora constrain H2O, CH4, NH3 abundances for each target with ten transits?
• RQ2 What is Pandora's ability to recover atmospheric temperature and metallicity given clouds/hazes?
• RQ3 How does combining Pandora with JWST improve constraints on atmospheric composition relative to JWST alone?
• RQ4 What is the minimum number of transits Pandora requires to detect atmospheric features above a flat-spectrum baseline for targets of varying brightness?
• RQ5 How do optical and NIR observations from Pandora help break degeneracies in retrievals?

Key findings

• Pandora can constrain H2O abundances to ≲1 dex for most targets with ten transits, though clouds/hazes introduce degeneracies.
• CH4 and NH3 abundances are less robustly constrained; CH4 can reach ≲1 dex in methane-dominated atmospheres, while NH3 remains less favored in model comparisons.
• Atmospheric temperature can be constrained to ~100 K even with high cloud coverage.
• Pandora can constrain atmospheric metallicity to ≲1 dex with ten transits, enabling population-level studies.
• Scattering slopes and aerosol properties can be partially characterized; strong slope enhancements (log(a) ≳ 6) are detectable with Pandora/NIRDA in some cases (e.g., K2-18 b).
• Bayesian model comparisons yield strong evidence for H2O presence (ln B ranging up to 544.3 for HD 209458 b) but weaker evidence for CH4 and NH3 across targets.
• Multi-transit observations improve parameter posteriors; adding transits yields diminishing returns after about ten transits for some parameters (e.g., H2O).
• SNR estimates show Pandora can achieve >5 SNR for the 1.4 μm H2O band around brighter stars (mJ ≤ 10), with higher SNRs for favorable targets.

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 $R\simeq 30$ . Different stellar fluxes and detector properties at different wavelengths will lead to differen