Every night, telescopes around the world capture millions of photons from distant stars, but extracting meaningful measurements from these raw images requires sophisticated processing pipelines. The RAPAS Photometry Pipeline addresses this fundamental challenge in observational astronomy by providing a complete workflow from image acquisition to calibrated photometric measurements. Whether you’re tracking variable stars, hunting for transients, or conducting stellar surveys, this pipeline handles the complex mathematics of transforming pixel values into astronomical magnitudes.
Built around a modern Streamlit interface, RAPAS combines multiple photometry techniques including aperture photometry with configurable radii and advanced PSF modeling using effective Point Spread Function fitting. The pipeline automatically solves astrometric coordinates using local Astrometry.net integration, performs sophisticated background modeling with the SExtractor algorithm, and cross-matches detections against nine major astronomical catalogs including GAIA DR3, SIMBAD, and the AAVSO Variable Star Index. Advanced features include cosmic ray removal via L.A.Cosmic, transient detection using survey templates, and comprehensive error propagation throughout the photometric chain.
This toolkit serves professional astronomers conducting photometric surveys, graduate students learning observational techniques, and citizen scientists contributing to variable star research. The real-time web interface makes complex astronomical processing accessible while maintaining the precision required for scientific publication. With support for multiple filter systems and robust outlier rejection algorithms, RAPAS represents a significant step toward democratizing high-quality astronomical photometry.
⭐ Stars: 4
💻 Language: Python
🔗 Repository: pierfra-rocci/rpp