Good news: astronomers are getting new tools to let them see further, better than ever before. The bad news: they’ll soon be getting more data than humans can handle.
To turn the vast quantities of data that will be pouring out of these instruments into world-changing scientific discoveries, Brant Robertson, a visiting professor at Princeton’s Institute for Advanced Studies and an associate professor of astronomy at UC Santa Cruz, is turning to AI.
“Astronomy is on the cusp of a new data revolution,” he said told a packed room at this week’s GPU Technology Conference in Silicon Valley.
Better Eyes on the Sky
Within a few years the range of instruments available to the world’s star-gazers will give them once unimaginable capabilities. Measuring an enormous 6.5 meters across, the James Webb Space Telescope — which will be deployed by NASA, the U.S. space agency, will be sensitive enough to give us a peek back at galaxies formed just a few hundred million years after the Big Bang.
The Large Synoptic Survey Telescope gets less press, but it has astronomers equally excited. The telescope, largely funded by the U.S. National Science Foundation and the Department of Energy, and being built on a mountaintop in Chile, will let astronomers survey the entire southern sky every three nights. This will produce a massive amount of data — 10 terabytes a night.
Finally, the Wide Field Infrared Survey Telescope puts an enormous digital camera into space. With origins in the U.S. spy satellite program, the satellite’s features will include a 288-megapixel, multi-band, near-infrared camera with a field of view 100x larger than that of the Hubble Space Telescope.
‘Richly Complex’ Data
Together, these three instruments will generate vast quantities of “richly complex” data, Robertson said. “We want to take that information and learn as much as we can,” he said. “Both from individual pixels and by aggregating them together.”
It’s a task far too large for humans alone. To keep up, Robertson is turning to AI. Created by Ryan Hausen, a Ph.D. student in UC Santa Cruz’s computer science department, Morpheus — a deep learning framework classifies astronomical objects, such as galaxies, based on the raw data streaming out of telescopes — such as the Hubble — on a pixel by pixel basis.
“In astronomy, we really do care about the technological advances that people in this room are engineering,” Robertson told his audience at GTC.
Translation: to find new stars in outer space, this prominent astrophysicist is looking, first, to deep learning stars here on Earth for help.
Image credit: NASA.