New planet on distant star discovered via artificial intelligence

Using machine learning, NASA and Google were able to discover two additional exoplanets circling Kepler-90 - one named Kepler-90i and the other Kepler-80g. Kepler-90i's surface temperature is 426 Celsius. The research paper reporting this finding has been accepted for publication in The Astronomical Journal.

"Kepler 90i is a G0 star a bit lighter than our Sun", said Vanderburg.

"Its surface is likely far too hot".

Kepler-90 is a Sun-like star, but all of its eight planets are scrunched into the equivalent distance of Earth to the Sun.

The Kepler telescope - which is essentially a traveling space camera - was launched in the spring of 2009 and has since been beaming images of deep space back to NASA. After finding thousands of exoplanets in a tiny area of the night sky near the constellation of Lyra over the Milky Way, Kepler's gyroscopes were damaged in 2014. So far it's found 2,525 planets in total.

The researchers say they plan to use the same method to search the remaining 150,000 stars the Kepler space telescope has studied so far.

In fact, as discoveries continue, he said there may come a day when our eight-planet system will seem small. He followed that it's similar to the way that a computer might learn to identify cats and dogs. The computer creates a neural network like the human brain.

So how exactly did Google's AI discover these planets?

On December 14 NASA announced that it has discovered two new exoplanets with a little help from Google. "It can be used to classify inputs, in this case signals from the Kepler telescope, as either planet, or not planet".

But we did manage to talk to one. After enough practice, they let it loose on light recordings captured by Kepler.

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. They thought the machine to recognise and distinguish patterns caused by actual planets and patterns caused by starspots and binary stars.

The discovery of a new planet orbiting a distant star means there is another solar system a lot like ours.

There is now an explosion of interest in machine learning and artificial intelligence, and since the dataset used here is pretty small, it's a big deal - particularly for astronomy.

Googles's AI is programmed rather differently, using machine learning. The next step is unsupervised machine learning.

Shallue is a senior software engineer at Google who suggested the application of a neural network to Kepler data. These planets had weak signals missed by previous searches of the stars.

"From the millions of data recieved from Kepler, the programmers trained the computer to pick up specific clues regarding orbit calculation, sense change in brightness when a planet passes across etc., and apply certain algorithms for detection of exoplanets".

Neither NASA nor Google expect to put astronomers out of business. "What we've developed here is a tool to enable astronomers to have more impact, to increase the productivity and it certainly won't replace them", said Shallue.

NASA astrophysicist Jessie Dotson, the Kepler project scientist, is "so excited to see where this goes next".

Kepler's successor, the Transiting Exoplanet Survey Satellite (TESS) will be launching this coming March.

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