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A low-density ocean inside Titan inferred from Cassini data

An Author Correction to this article was published on 14 May 2024

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Abstract

The Cassini mission has provided measurements of the gravity of several moons of Saturn as well as an estimate of the tidal response, which is expressed as the degree 2 Love number k2 of its largest moon, Titan. The first estimates of Titan’s Love number were larger than pre-Cassini expectations. Interior modelling suggested it may be explained with a dense ocean, but the interpretation remains unclear. We analysed Cassini tracking data to determine Titan’s gravity field and its Love number. Our gravity results are consistent with earlier studies, but we find a lower Love number for Titan of k2 = 0.375 ± 0.06. This lower value follows from an elaborate investigation of the tidal effects. We show that a dense ocean is not implied by the obtained Love number; instead, a water or ammonia ocean is more probable. A lower density ocean can increase the likeliness of contact between the silicate core and ocean, which can leach minerals into the ocean and could promote its habitability.

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Fig. 1: Titan’s gravity expressed as radial accelerations.
Fig. 2: RMS power for Titan’s gravity.
Fig. 3: Properties of Titan’s core.
Fig. 4: Ocean density versus Love number k2 for Titan.

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Data availability

Cassini radio tracking data and ancillary information can be found at the Planetary Data System’s Atmospheres node (https://pds-atmospheres.nmsu.edu/data_and_services/atmospheres_data/Cassini/inst-rss.html). Results from our analysis such as the gravity field models and output from our MCMC modelling are available via NASA’s Planetary Geodesy Data Archive at https://pgda.gsfc.nasa.gov/products/91 or https://doi.org/10.60903/gsfcpgda-titank2.

Code availability

We used the open source software TidalPy to analyse Titan’s Love number (https://doi.org/10.5281/zenodo.7017474 (ref. 43)) and the emcee open source software32 for our MCMC analysis (https://emcee.readthedocs.io/en/stable/). We also used the PlanetProfile software44 (https://github.com/vancesteven/PlanetProfile) to compute the self-consistent interior models for Titan used in our modelling. The input data for the MCMC analysis are the results presented in this work; additional input parameters for TidalPy are discussed in the text and listed in Supplementary Table 4. We also used the Python package corner45 for the distribution plot in Supplementary Information. We cannot provide the software used for the analysis of the Cassini tracking data, but the methods have long been established and are described in detail in Methods. All figures (apart from the distribution plot in Supplementary Fig. 5) were drawn with the free software GMT (https://www.generic-mapping-tools.org/)46.

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Acknowledgements

This work was funded by NASA’s Cassini Data Analysis Program (S.G., B.v.N. and E.M.). We thank T. Sabaka (NASA/GSFC), S. Bertone (NASA/GSFC, University of Maryland, Baltimore County, and CRESST II), W. Henning and J. Renaud (NASA/GSFC, University of Maryland and CRESST II), G. Cascioli (NASA/GSFC and University of Maryland, Baltimore County), and D. Durante and L. Iess (Sapienza University of Rome, Italy) for discussions.

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Contributions

S.G. and E.M. conceived and designed the study. S.G., B.v.N. and A.M. analysed the Cassini tracking data. E.M. supported the analysis of the Cassini tracking data. W.v.d.W. provided theoretical support. All authors contributed to the discussion and interpretation of the results. S.G. wrote the first draft of the paper. All authors contributed to subsequent drafts.

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Correspondence to Sander Goossens.

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Nature Astronomy thanks Sebastien Le Maistre, Marzia Parisi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–13, Tables 1–4 and references.

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Goossens, S., van Noort, B., Mateo, A. et al. A low-density ocean inside Titan inferred from Cassini data. Nat Astron (2024). https://doi.org/10.1038/s41550-024-02253-4

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