Water-hydrogen demixing occurs on warm sub-Neptunes with envelope metallicities of 150-700 times solar, including TOI-270 d, implying layered interiors and underestimated bulk metallicities when using fully-miscible models.
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Photoevaporative and collisional mass losses diversify exoplanet parameter space in ways consistent with standard core accretion, enabling an expanded eight-class classification scheme.
Models coupling hydrogen-silicate-iron miscibility with atmospheric escape reproduce the observed mass-radius occurrence density of sub-Neptunes and super-Earths.
The paper reviews ML applications for sequence modeling, pattern recognition, and generative Bayesian analysis to tackle heterogeneous data challenges in (exo)planetary science.
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Machine Learning as a Transformative Tool for (Exo-)Planetary Science
The paper reviews ML applications for sequence modeling, pattern recognition, and generative Bayesian analysis to tackle heterogeneous data challenges in (exo)planetary science.