When a star explodes in a distant galaxy or a variable object flickers in the night sky, astronomers race against time to capture its changing brightness. Traditional photometry—the precise measurement of astronomical brightness—has long been a bottleneck, requiring hours of manual image processing for each observation. AutoPhOT eliminates this constraint, transforming raw CCD and near-infrared images into publication-quality light curves with minimal human intervention.
This Python pipeline orchestrates a sophisticated workflow that would typically require multiple specialized tools and expert knowledge. It automatically solves world coordinate systems, removes cosmic rays, subtracts backgrounds, and performs both aperture and PSF photometry using enhanced point spread functions. The system intelligently calibrates against major stellar catalogs like Gaia and Pan-STARRS, while its template subtraction capabilities—powered by algorithms like SFFT, HOTPANTS, or ZOGY—can isolate transient signals from static sky backgrounds. Perhaps most impressively, it determines limiting magnitudes through injection-recovery testing, providing crucial statistical bounds for non-detections.
With 34 stars on GitHub and a peer-reviewed foundation, AutoPhOT is already accelerating discovery timelines for time-domain astronomy surveys. Whether you’re tracking supernovae for dark energy studies, monitoring variable stars for stellar physics, or hunting for optical counterparts to gravitational wave events, this tool transforms weeks of manual analysis into automated overnight processing, letting astronomers focus on the science rather than the data reduction.
⭐ Stars: 34
💻 Language: Python
🔗 Repository: Astro-Sean/autophot