Issue |
A&A
Volume 692, December 2024
|
|
---|---|---|
Article Number | A251 | |
Number of page(s) | 11 | |
Section | Planets, planetary systems, and small bodies | |
DOI | https://doi.org/10.1051/0004-6361/202452383 | |
Published online | 18 December 2024 |
Characterizing Jupiter’s interior using machine learning reveals four key structures
1
Department of Earth and Planetary Sciences, Weizmann Institute of Science,
Rehovot
76100,
Israel
2
Institut für Astrophysik, Universität Zürich,
Winterthurerstr. 190,
8057
Zürich,
Switzerland
3
Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange,
06304
Nice Cedex 4,
France
★ Corresponding author; maayan.ziv@weizmann.ac.il
Received:
26
September
2024
Accepted:
12
November
2024
Context. The internal structure of Jupiter is constrained by the precise gravity field measurements by NASA’s Juno mission, atmospheric data from the Galileo entry probe, and Voyager radio occultations. Not only are these observations few compared to the possible interior setups and their multiple controlling parameters, but they remain challenging to reconcile. As a complex, multidimensional problem, characterizing typical structures can help simplify the modeling process.
Aims. We explored the plausible range of Jupiter’s interior structures using a coupled interior and wind model, identifying key structures and effective parameters to simplify its multidimensional representation.
Methods. We used NeuralCMS, a deep learning model based on the accurate concentric Maclaurin spheroid (CMS) method, coupled with a fully consistent wind model to efficiently explore a wide range of interior models without prior assumptions. We then identified those consistent with the measurements and clustered the plausible combinations of parameters controlling the interior.
Results. We determine the plausible ranges of internal structures and the dynamical contributions to Jupiter’s gravity field. Four typical interior structures are identified, characterized by their envelope and core properties. This reduces the dimensionality of Jupiter’s interior to only two effective parameters. Within the reduced 2D phase space, we show that the most observationally constrained structures fall within one of the key structures, but they require a higher 1 bar temperature than the observed value.
Conclusions. We provide a robust framework for characterizing giant planet interiors with consistent wind treatment, demonstrating that for Jupiter, wind constraints strongly impact the gravity harmonics while the interior parameter distribution remains largely unchanged. Importantly, we find that Jupiter’s interior can be described by two effective parameters that clearly distinguish the four characteristic structures and conclude that atmospheric measurements may not fully represent the entire envelope.
Key words: methods: numerical / planets and satellites: composition / planets and satellites: gaseous planets / planets and satellites: interiors / planets and satellites: individual: Jupiter
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.