When a star passes precisely in front of another star, Einstein’s theory of general relativity creates a natural cosmic telescope—gravitational microlensing can magnify distant light and reveal hidden exoplanets orbiting the foreground star. The upcoming Roman Space Telescope will monitor millions of stars in our galaxy’s bulge, potentially discovering thousands of new worlds through these rare alignment events. This repository prepares the astronomical community for that data deluge through the Roman Microlensing Data Challenge 2026.
These comprehensive Jupyter notebooks guide researchers through the complete microlensing analysis pipeline using real open-source tools and simulated Roman telescope data. The collection includes hands-on tutorials for fitting light curves, modeling planetary signals, and scaling analysis workflows for the massive datasets Roman will produce. From basic microlensing physics to advanced statistical techniques, each notebook runs seamlessly in Google Colab or local environments, complete with installation guides and dependency management for popular packages like MulensModel and pyLIMA.
Developed by the Roman Galactic Exoplanet Survey Project Infrastructure Team (RGES-PIT), these resources serve both seasoned microlensing experts and newcomers to the field. The challenge encourages fresh talent to join exoplanet research while advancing the computational methods needed to extract maximum science from Roman’s unprecedented survey of our galaxy’s hidden planetary population.
⭐ Stars: 4
💻 Language: Jupyter Notebook
🔗 Repository: rges-pit/data-challenge-notebooks