An astrophysicist used Claude Science to build the first complete ultraviolet map of the sky
An astrophysicist worked with Claude Science to create the first complete ultraviolet map of the sky. Astronomers have already created complete sky maps from radio to gamma rays. But large regions of the sky have never been observed in UV. In today’s science blog, Brice Ménard explains how he guided Claude to find existing datasets, combine them, and fill in the gaps with statistical inference. The work would have taken humans weeks of work, but, with Claude, just took a few days while Ménard worked on other projects. The resulting map is a useful teaching tool and an example of exactly the sort of slow, low-priority work which scientists never quite get around to, but which AI now makes feasible. Read more:
Context
It shows AI agents taking on the slow, low priority data work that scientists rarely get to, finishing in days what Anthropic says would have taken a person weeks.
Ultraviolet light is absorbed by the ozone layer, so the UV sky can only be observed from space, and about a third of it has never been observed. NASA's GALEX mission imaged about two thirds of the sky from 2003 to 2013 but deliberately skipped areas with very bright stars, including much of the Milky Way's plane. Brice Ménard, who wrote the post, is an astrophysicist at Johns Hopkins University and a researcher at Anthropic.
Deep dive
In Anthropic's science blog, Ménard describes asking Claude Science to gather every available UV dataset, put them on a common scale, merge them into one map and fill in every patch of sky no UV telescope has observed. According to the post, Claude orchestrated a team of agents that found and downloaded public surveys, including tens of thousands of GALEX images, removed glare around bright stars and cross calibrated data from different telescopes.
To fill the gaps, Claude used inpainting combined with observations at other wavelengths. Using the two thirds of the sky mapped in UV, it learned how UV brightness relates to visible, infrared and radio data, then estimated the missing third along with uncertainty estimates. In tests where known regions were hidden, Ménard says the model estimated the hidden data to within about 10% of real measurements. Claude then added UV estimates for more than 100 million stars based on data from ESA's Gaia satellite.
The post says Claude did not get everything right the first time. Ménard spotted faint circles left by individual GALEX observations, an error that had passed two rounds of review by other agents, and Claude then corrected it across all 38,000 observations.
Ménard says they produced more than a dozen versions of the map over several days while he worked on other projects. Each pixel of the final map is labeled as measured or predicted, and about a third of the map, including much of the galactic plane, is predicted rather than observed.
What to expect next
Ménard presents the map as a teaching tool, so watch whether astronomers adopt it in courses and how they treat the predicted third of the sky, which comes with uncertainty estimates rather than measurements.
The broader question is whether Claude Science and similar tools are used for other backlogged projects. Ménard writes that many scientists can think of a map, figure or resource they have been putting off for the same reason.