LOC:
Fran Pozuelos (IAA-CSIC)
Laura Darriba (IAA-CSIC)
Javier Moldón (IAA-CSIC)
Within the Severo Ochoa Training Initiative of the IAA-CSIC we are offering short introductory practical courses about Python packages for astrophysical applications (PySnacks). We invite you to participate in the 4h course PySnack 9: GASTLI
Understanding the interior composition of exoplanets is key to uncovering their formation and evolutionary histories, especially their metal content. By comparing observed mass and radius measurements with interior structure and evolution models, we can infer a planet’s metal mass fraction. With the advent of JWST, CHEOPS, TESS, and the upcoming PLATO, we are entering an era of unprecedented precision in exoplanet radius, age, and atmospheric metallicity measurements.
To harness this growing wealth of data, we introduce GASTLI (GAS gianT modeL for Interiors) — a user-friendly, open-source Python package designed to make interior modeling accessible. GASTLI is optimized for rapid computation of mass-radius and radius-luminosity-age relationships and enables interior composition retrievals to fit models to observed mass, radius, age, and, when available, atmospheric metallicity.
Supporting a diverse range of planetary compositions, masses, and irradiation conditions, GASTLI is ideal for modeling planets from warm sub-Neptunes to hot gas giants. It incorporates state-of-the-art thermodynamic data and equations of state for rock, water, and hydrogen/helium, alongside a customizable atmospheric grid feature, ensuring accurate representation of high-pressure planetary envelopes.
This course will be taught by Lorena Acuña (MPIA-Heidelberg).