Every world in the cosmos tells a story written in tidal forces. When celestial bodies orbit close together, gravitational tugs create internal friction that can melt ice, drive volcanism, and reshape entire planetary interiors. Understanding these tidal processes is crucial for determining which worlds might harbor subsurface oceans, predicting orbital evolution, and unlocking the thermal histories of everything from Jupiter’s moons to distant exoplanets.
TidalPy transforms this complex physics into accessible computational tools. Built with a semi-analytic approach in Python and optimized with Cython, it calculates tidal heating rates, Love numbers for multi-layered worlds, spin-orbit resonances, and thermal evolution pathways. The RadialSolver package stands out for its ability to model viscoelastic responses in rocky and icy bodies, accounting for liquid layers, compressibility, dynamic tides, and sophisticated rheological models that capture how materials behave under extreme conditions.
From Mercury’s core dynamics to the subsurface seas of icy moons, TidalPy has already proven its worth across our Solar System and beyond. Researchers use it to explore exoplanetary systems, predict which worlds might maintain liquid water, and understand how tidal interactions drive long-term planetary evolution. With comprehensive documentation, cross-platform compatibility, and active development, it’s becoming an essential tool for anyone studying the gravitational choreography that shapes worlds throughout the universe.
⭐ Stars: 23
💻 Language: Jupyter Notebook
🔗 Repository: jrenaud90/TidalPy