Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light years from Earth. The planet was discovered in data from NASA's Kepler Space Telescope.
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| The Kepler-90 planets have a similar configuration to our solar system with small planets found orbiting close to their star, and the larger planets found farther away. In our solar system, this pattern is often seen as evidence that the outer planets formed in a cooler part of the solar system, where water ice can stay solid and clump together to make bigger and bigger planets. The pattern we see around Kepler-90 could be evidence of that same process happening in this system [Credit: NASA/Ames Research Center/Wendy Stenzel] |
"Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them," said Paul Hertz, director of NASA's Astrophysics Division in Washington. "This finding shows that our data will be a treasure trove available to innovative researchers for years to come."
The discovery came about after researchers Christopher Shallue and Andrew Vanderburg trained a computer to learn how to identify exoplanets in the light readings recorded by Kepler -- the miniscule change in brightness captured when a planet passed in front of, or transited, a star. Inspired by the way neurons connect in the human brain, this artificial "neural network" sifted through Kepler data and found weak transit signals from a previously-missed eighth planet orbiting Kepler-90, in the constellation Draco.
Machine learning has previously been used in searches of the Kepler database, and this continuing research demonstrates that neural networks are a promising tool in finding some of the weakest signals of distant worlds.
Other planetary systems probably hold more promise for life than Kepler-90. About 30 percent larger than Earth, Kepler-90i is so close to its star that its average surface temperature is believed to exceed 800 degrees Fahrenheit, on par with Mercury. Its outermost planet, Kepler-90h, orbits at a similar distance to its star as Earth does to the Sun.
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| With the discovery of an eighth planet, the Kepler-90 system is the first to tie with our solar system in number of planets. Artist's concept [Credit: NASA/Ames Research Center/Wendy Stenzel] |
Shallue, a senior software engineer with Google's research team Google AI, came up with the idea to apply a neural network to Kepler data. He became interested in exoplanet discovery after learning that astronomy, like other branches of science, is rapidly being inundated with data as the technology for data collection from space advances.
"In my spare time, I started Googling for 'finding exoplanets with large data sets' and found out about the Kepler mission and the huge data set available," said Shallue. "Machine learning really shines in situations where there is so much data that humans can't search it for themselves."
Kepler's four-year dataset consists of 35,000 possible planetary signals. Automated tests, and sometimes human eyes, are used to verify the most promising signals in the data. However, the weakest signals often are missed using these methods. Shallue and Vanderburg thought there could be more interesting exoplanet discoveries faintly lurking in the data.
First, they trained the neural network to identify transiting exoplanets using a set of 15,000 previously vetted signals from the Kepler exoplanet catalogue. In the test set, the neural network correctly identified true planets and false positives 96 percent of the time. Then, with the neural network having "learned" 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. "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."
Kepler-90i wasn't the only jewel this neural network sifted out. In the Kepler-80 system, they found a sixth planet. This one, the Earth-sized Kepler-80g, and four of its neighboring planets form what is called a resonant chain -- where planets are locked by their mutual gravity in a rhythmic orbital dance. The result is an extremely stable system, similar to the seven planets in the TRAPPIST-1 system.
Their research paper reporting these findings has been accepted for publication in The Astronomical Journal. Shallue and Vanderburg plan to apply their neural network to Kepler's full set of more than 150,000 stars.
Kepler has produced an unprecedented data set for exoplanet hunting. After gazing at one patch of space for four years, the spacecraft now is operating on an extended mission and switches its field of view every 80 days.
"These results demonstrate the enduring value of Kepler's mission," said Jessie Dotson, Kepler's project scientist at NASA's Ames Research Center in California's Silicon Valley. "New ways of looking at the data -- such as this early-stage research to apply machine learning algorithms -- promise to continue to yield significant advances in our understanding of planetary systems around other stars. I'm sure there are more firsts in the data waiting for people to find them."
Author: Rebecca Johnson | Source: NASA/Jet Propulsion Laboratory [December 14, 2017]
