NeuralCMS: A deep learning approach to study Jupiter’s interior
M. Ziv,
E. Galanti,
A. Sheffer
et al.
Abstract:NASA's Juno mission provided exquisite measurements of Jupiter's gravity field that together with the Galileo entry probe atmospheric measurements constrains the interior structure of the giant planet. Inferring its interior structure range remains a challenging inverse problem requiring a computationally intensive search of combinations of various planetary properties, such as the cloud-level temperature, composition, and core features, requiring the computation of sim \(10^9\) interior models. We propose an … Show more
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