Young sub-Neptunes transition from core-powered bolometric escape to photoevaporative escape at smaller radii for lower-mass and more irradiated planets, with self-consistent simulations yielding combined mass-loss rates and analytic transition scalings.
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Simulations tie the deep-mantle primordial neon reservoir to an initial embryo mass of ~0.3 Earth masses assembled during solar-nebula dispersal.
Variable hydrogen-silicate-iron miscibility coupled with atmospheric escape reproduces the occurrence density structure, radius gap, and radius-period relation of sub-Neptunes and super-Earths based on accreted hydrogen fraction.
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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Characterizing the bolometric-photoevaporative transition in young sub-Neptunes with radiation-hydrodynamic simulations
Young sub-Neptunes transition from core-powered bolometric escape to photoevaporative escape at smaller radii for lower-mass and more irradiated planets, with self-consistent simulations yielding combined mass-loss rates and analytic transition scalings.
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Constructing Earth Formation History Using Deep Mantle Noble Gas Reservoirs
Simulations tie the deep-mantle primordial neon reservoir to an initial embryo mass of ~0.3 Earth masses assembled during solar-nebula dispersal.
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The Influences of Hydrogen-Silicate-Iron Miscibility on the Demographics of Sub-Neptunes and Super-Earths
Variable hydrogen-silicate-iron miscibility coupled with atmospheric escape reproduces the occurrence density structure, radius gap, and radius-period relation of sub-Neptunes and super-Earths based on accreted hydrogen fraction.
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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.