Understanding the fundamental properties of young stellar and substellar objects has long been one of astronomy’s most challenging puzzles. These cosmic infants are still shrouded in the complexities of their birth environments, making accurate age and mass determinations incredibly difficult. Yet these parameters are crucial for everything from exoplanet characterization to stellar evolution studies.
MADYS (Manifold Age Determination for Young Stars) transforms this challenge into an elegant solution by automatically retrieving photometry from multiple catalogs, cross-matching with Gaia data, and performing sophisticated isochronal fitting across 21 stellar evolution models and 153 isochrone grids. The tool’s taxonomical classification system brings order to the chaos of heterogeneous model formats, while its six specialized classes handle applications from directly-imaged exoplanet characterization to stellar association studies. Perhaps most exciting is its DetectionMap functionality, which converts contrast curves from direct imaging surveys into planetary mass detection limits and probability maps.
Direct imaging surveys are already leveraging MADYS to push the boundaries of exoplanet detection, while stellar astronomers use it to decode the properties of young stellar associations. With continuous updates adding new models and filters, MADYS represents the kind of community-driven tool that accelerates discovery across the field, turning months of manual catalog cross-matching into automated, reproducible science.
⭐ Stars: 7
💻 Language: Python
🔗 Repository: vsquicciarini/madys