Inferring Mimas' spatial distribution of tidal heating from its long-wavelength topography

In new work (Gyalay et al., 2023), we infer the interior of Mimas from its global shape (long-wavelength topography). To do so, we have to make various assumptions on how the ice shell of Mimas operates. This includes the temperature at the base of the ice shell, the thickness of the ice shell, what mode of isostasy it operates under (equal-mass vs. equal-pressure and Airy vs. Pratt), whether tidal tidal heating is due to eccentricity vs. obliquity, and how porous the region of the ice shell with a temperature <140 K may be. Further, as it has not yet been measured for Mimas, we must make an assumption on its moment of inertia. We vary through these assumptions and calculate how well an inferred heat distribution matches with a tidal heating distribution, among other physical self-consistency checks. In the associated paper, we analyze the dataset we produced to make conclusions on Mimas' interior structure and orbital dynamic history.

Methods
This dataset was produced by a model using the methods described in Gyalay & Nimmo (2023a; JGR: Planets 128(2), doi: 10.1029/2022JE007550). In that paper, we established the mathematics behind how we used assumed parameters (upper ice shell porosity, total ice shell thickness, moment of inertia, basal temperature at the base of the ice shell) to infer the average basal heat flux and fit for spatial patterns of tidal heating (Beuthe, 2013, Icarus). Using this best-fit tidal heating for each set of parameters, we forward model the topography (also described in that paper) and calculate its spherical harmonic weights as well as compare them to the originally observed topography.

The code used to generate this dataset and as well as the dataset associated with Gyalay & Nimmo (2023a) are included in that paper's associated repository (Gyalay & Nimmo, 2023b; Dryad, dataset, doi: doi.org/10.7291/D11969). This repository contains only the produced model output for Mimas.