The Legacy Survey of Space and Time (LSST) will revolutionize our understanding of the solar system, potentially discovering millions of asteroids, comets, and trans-Neptunian objects. But how do you prepare for such an astronomical treasure trove? How do you test detection algorithms, plan observing strategies, or predict what discoveries await? Enter Sorcha - an open-source simulator that lets you peek into LSST’s future by modeling exactly what the telescope will observe across our cosmic neighborhood.
Built in Python and powered by AstroPy, Sorcha takes orbital dynamics and transforms them into realistic observational data. It simulates everything from main-belt asteroids to distant Kuiper Belt objects, accounting for realistic observing conditions, detection limits, and survey cadences. The simulator handles complex photometric modeling, applies observational uncertainties, and even includes realistic sky backgrounds and weather effects. Whether you’re developing machine learning pipelines for moving object detection or planning follow-up observations for potentially hazardous asteroids, Sorcha provides the synthetic datasets you need.
This isn’t just academic software gathering digital dust - it’s a collaborative effort between major institutions including the University of Washington’s DiRAC Institute, Queen’s University Belfast, and Harvard-Smithsonian Center for Astrophysics. With comprehensive documentation, conda-forge distribution, and active development, Sorcha is ready for both seasoned solar system researchers and developers diving into astronomical simulation for the first time.
⭐ Stars: 27
💻 Language: Python
🔗 Repository: dirac-institute/sorcha