Using Claude Science to produce the first complete map of the sky in UV light

This post details the application of AI agents, orchestrated through Claude Science, to a complex scientific data processing task: the creation of a complete UV light map of the sky. It showcases the agents' ability to search for and download astronomical survey data, perform internal consistency checks and glare removal around stars, cross-calibrate and merge data from different instruments, and use inpainting techniques (informed by multi-wavelength data) to fill in unobserved regions. A specific failure mode (visible "discs" from individual observations due to residual atmospheric glow) and its subsequent correction by the agents based on human feedback is also described, demonstrating an iterative refinement process. The contribution highlights the agents' capability in handling large datasets, complex calibration, and sophisticated data imputation for scientific discovery.