A fully Bayesian pixel-based Doppler imaging framework uses Gaussian Process priors and Hamiltonian Monte Carlo to simultaneously infer surface maps and geometric parameters from spectral data.
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Climate states on exoplanets with the same atmospheric composition create different reflectance spectra, changing the detectability of atmospheric features and biosignatures, with seasonal variations on high-obliquity worlds adding time-dependent signals.
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Bayesian Doppler Imaging: Simultaneous Inference of Surface Maps and Geometric Parameters
A fully Bayesian pixel-based Doppler imaging framework uses Gaussian Process priors and Hamiltonian Monte Carlo to simultaneously infer surface maps and geometric parameters from spectral data.
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Impact of Climate States and Seasons on Future Exo-Earth Observations
Climate states on exoplanets with the same atmospheric composition create different reflectance spectra, changing the detectability of atmospheric features and biosignatures, with seasonal variations on high-obliquity worlds adding time-dependent signals.