NASA's $\textit{Pandora SmallSat Mission}$: 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. Bayesian retrievals of joint visible photometry and NIR spectroscopy 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.

Figures (5)

• Figure 1: Simulated time-dependent spot filling factors for each stellar scenario. Each panel shows sinusoidal variations in the projected spot filling factor over a full 30-day observing window, using the adopted stellar rotation period (5 or 30 d) and the $f_{\mathrm{min}}$ and $f_{\mathrm{max}}$ values from \ref{['tab:spot_coverage']}. Thicker line segments show the times of the simulated Pandora observations.
• Figure 2: Representative simulated Pandora spectra for each stellar scenario. Each row corresponds to a stellar scenario, while the left and right columns show count rate and flux density, respectively. In each panel, a representative 12-hr binned spectrum is shown for both giant spot (red) and solar-like spot (orange) morphologies. Vertical error bars, which are generally smaller than the line width, denote 12-hr measurement uncertainties. The dotted black curves indicate the sensitivity of the VISDA and NIRDA instruments, shown on an arbitrary scale.
• Figure 3: Time series of inferred stellar parameters from fits to simulated Pandora observations of K-dwarf targets under four variability scenarios. Panels show the recovered photospheric temperature ($T\mathrm{phot}$), spot temperature ($T_\mathrm{spot}$), spot filling factor ($f_\mathrm{spot}$), and stellar radius ($R_\star$) as a function of time. Each point corresponds to a pre- or post-transit stellar spectrum from an individual 24-hr visit. Black boxes indicate the input (true) parameter values. Blue points show the posterior means from the two-component retrievals, with error bars denoting the 68% credible intervals. Orange points indicate datasets for which the one-component model is preferred, for which $T_\mathrm{spot}$ and $f_\mathrm{spot}$ are not defined.
• Figure 4: Time series of inferred stellar parameters from fits to simulated Pandora observations of M-dwarf targets under four variability scenarios. The figure elements are the same as in \ref{['fig:inferences_K']}.
• Figure 5: True and residual stellar contamination signals for the spot prescriptions we consider: giant spots (top), solar-like spots with maximum contamination (middle), and solar-like spots with moderate contamination (bottom). In each row, columns correspond to the four related scenarios (see \ref{['tab:scenarios']}). Upper subpanels show the true contamination signal, $\Delta D(\lambda)$, across the VISDA bandpass (points with horizontal error bars) and the NIRDA wavelength range (curves). All 20 epochs are shown, and colors encode the epoch time. Lower subpanels show the residual contamination, $\Delta D_{\rm resid}(\lambda)$, remaining after applying the inferred correction, with shaded regions indicating the propagated uncertainty from the stellar retrieval posteriors.