The same technology that suggests movies or TV shows that you might want to watch is helping astronomers. Machine learning is a growing field that takes large amounts of data and finds patterns that humans (except maybe Dr. Spencer Reid from "Criminal Minds") might not see.
Astronomers are using machines to help identify basic star properties. Instead of relying on a spectrum analysis of the different wavelengths of starlight, computer algorithms flip through the images and pick up on the patterns that classify a star.
The method promises information processing in less time for less money.
"It's like video-streaming services not only predicting what you would like to watch in the future, but also your current age, based on your viewing preferences," said Adam Miller of NASA's Jet Propulsion Laboratory in Pasadena, Calif. "We are predicting fundamental properties of the stars."
Miller presented the results of his report at the American Astronomical Society meeting in Seattle on Thursday, and the report will be published in the Astrophysical Journal.
"With more information about the different kinds of stars in our Milky Way galaxy, we can better map the galaxy's structure and history," said Miller.
"This is an exciting time to be applying advanced algorithms to astronomy," Miller later stated. "Machine learning allows us to mine for rare and obscure gems within the deep data sets that astronomers are only now beginning to acquire."
