PlanetProfile: Self‐Consistent Interior Structure Modeling for Ocean Worlds and Rocky Dwarf Planets in Python

Abstract

AbstractThe open‐source PlanetProfile framework was developed to investigate the interior structure of icy moons based on collectively matching their observed properties and comparative planetology. The software relates observed and measured properties, assumptions such as the type of materials present, and laboratory equation‐of‐state (EOS) data through geophysical and thermodynamic models to evaluate radial profiles of mechanical, thermodynamic, and electrical properties, as self‐consistently as possible. We have created a Python version of PlanetProfile. In the process, we have made optimization improvements and added parallelization and parameter‐space search features to utilize fast operation for investigating unresolved questions in planetary geophysics, in which many model inputs are poorly constrained. The Python version links to other scientific software packages, including for evaluating EOS data, magnetic induction calculations, and seismic calculations. Physical models in PlanetProfile have been reconfigured to improve self‐consistency and generate the most realistic relationships between properties. In this work, we focus on the description of the software design and algorithms in detail, summarize model results for major moons across the outer solar system, and discuss new inferences about the interior structure of several bodies. The high values and narrow uncertainty ranges reported for the axial moments of inertia for Callisto, Titan, and Io are difficult to reconcile with the realistic physical and chemical approximations applied, requiring highly porous rock layers equivalent to incomplete differentiation for Callisto and Titan, and a high rock melt fraction for Io. Radial profiles for each model and comparison to prior work are provided as Zenodo archives.