With over 35,000 possible planetary signals from Kepler, so far just over 2,500 have been confirmed as actual planets. Astronomers have looked at just the strongest signals from the 150,000 stars that the Kepler mission studied. But scientists knew there were other weaker signals hiding in the data with no humanly possible way to find them.
Shallue approached NASA and worked with Andrew Vanderburg, an astronomer at the University of Texas, Austin to train a computer to learn how to identify exoplanets, looking for extremely weak signals that might show a miniscule change in brightness captured when a planet passes in front of — or transited — a star.
“A neural network is a technique of machine learning that is loosely inspired by the structure of the human brain in which 'neurons' do a simple computation and then pass information to the next layer of neurons,” Shallue explained during the briefing. “In this way, a computer can ‘learn’ how to identify a dog from a cat, or an exoplanet from something else in the readings measured by space telescopes like Kepler.”
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The neural networks could be thought of as switches that turn on depending on the pathways that were created from previous data.
The team used the neural network to look at 15,000 signals that had been previously confirmed as either a planet or a false positive, and the network learned how to distinguish real planets from false signals.
Quickly, the computer advanced to finding the correct answer 96 percent of the time in testing.
Then, with the neural network having "learned" how to detect the pattern of a transiting exoplanet, the researchers directed their model to search for weaker signals in 670 star systems that already had multiple known planets. Their assumption was that multiple-planet systems would be the best places to look for more exoplanets.
“We got lots of false positives of planets, but also potentially more real planets,” said Vanderburg in a statement. “It’s like sifting through rocks to find jewels. If you have a finer sieve then you will catch more rocks but you might catch more jewels, as well."