Search Results for author:
Found 4 papers, 2 papers with code
Exoplanet Characterization using Conditional Invertible Neural Networks
Indeed, using cINNs allows for orders of magnitude faster inference of an exoplanet's composition than what is possible using an MCMC method, however, it still requires the computation of a large database of internal structures to train the cINN.
Internal water storage capacity of terrestrial planets and the effect of hydration on the M-R relation
Here we consider three types of planets: dry interiors, hydrated interiors and dry interiors + surface ocean where the ocean mass fraction corresponds to the mass fraction of $\rm H_2 O$ equivalent in the hydrated case.
Earth and Planetary Astrophysics
Using Deep Neural Networks to compute the mass of forming planets
Computing the mass of planetary envelopes and the critical mass beyond which planets accrete gas in a runaway fashion is important when studying planet formation, in particular for planets up to the Neptune mass range.
Earth and Planetary Astrophysics
The formation of Jupiter by hybrid pebble-planetesimal accretion
The evidence that Jupiter slowed down its growth after reaching 20 Earth masses for at least 2 Myr is puzzling because a planet of this mass is expected to trigger fast runaway gas accretion.
Earth and Planetary Astrophysics
