Google has previously discovered lost tribes, missing ships and even a forgotten forest. But now it has also found two entire planets.
The technology giant used one its algorithms to sift through thousands of signals sent back to Earth by Nasa’s Kepler space telescope.
One of the new planets was found hiding in the Kepler-90 star system, which is around 2,200 light years away from Earth.
The discovery is important because it takes the number of planets in the star system up to eight, the same as our own Solar System. It is the first time that any system has been found to have as many planets ours.
Andrew Vanderburg, astronomer and Nasa Sagan Postdoctoral Fellow at The University of Texas, Austin, said: “The Kepler-90 star system is like a mini version of our solar system.
You have small planets inside and big planets outside, but everything is scrunched in much closer.
“There is a lot of unexplored real estate in Kepler-90 system and it would almost be surprising if there were not more planets in the system.”
The planet Kepler-90i, is a small rocky planet, which orbits so close to its star that the surface temperature is a ‘scorchingly hot’ 800F (426C). It orbits its own sun once every 14 days.
The Google team applied a neural network to scan weak signals discovered by the Kepler exoplanet-hunting telescope which had been missed by humans.
Kepler has already discovered more than 2,500 exoplanets and 1,000 more which are suspected.
The telescope spent four years scanning 150,000 stars looking for dips in their brightness which might suggest an orbiting planet was passing in front.
Although the observation mission ended in 2013, the spacecraft recorded so much data during its four year mission that scientists expect will be crunching the data for many years to come.
Christopher Shallue, senior software engineer at Google AI in Mountain View, California, who made the discovery, said the algorithm was so simple that it only took two hours to train to spot exoplanets.
Test of the neural network correctly identified true planets and false positives 96 percent of the time. They have promised to release all of the code so that amateurs can train computers to hunt for their own exoplanets.
“Machine learning will become increasingly important for keeping pace with all this data and will help us make more discoveries than ever before,” said Mr Shallue.
“This is really exciting discovery and a successful proof of concept in using neural networks to find planets even in challenging situations where signals are very weak.
“We plan to search all 150,000 stars, we hope using our technique we will be able to find lots of planets including planets like Earth.”
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