NASA discovers new planet using Google AI

16 December, 2017, 05:59 | Author: Darren Santiago
  • Above An illustration shows how the planets in the Kepler-90 system compare to those in our own solar system. Image Credit NASA

After this discovery, the Kepler-90 solar system has come at par with our own in terms of number of planets revolving around a single star, said NASA.

The newly discovered eighth planet, called Kepler-90i, was found using machine learning from Google. The research paper reporting this finding has been accepted for publication in The Astronomical Journal. This exoplanet is locked together with four of its neighboring planets by their mutual gravity to form a "resonant chain", similar to the seven planets in the TRAPPIST-1 system.

An eighth planet called Keplar-90i has been found in a faraway solar system, matching our own in numbers.

A graphic showing all of Kepler-90's planets bunched near their star, in comparison to our solar system. "You have small planets inside and big planets outside, but everything is scrunched in much closer", said Vanderburg, a NASA Sagan Postdoctoral Fellow and astronomer at the University of Texas at Austin.

"There is a lot of unexplored real estate in the Kepler 90 system", said Vanderburg. And these planets resemble those around us: rocky planets circling in orbit near the star, with gas giants farther away.

Since launching in 2009, Kepler has watched more than 150,000 stars in one part of the sky to determine exoplanet candidates, based on the slight dimming of stars as potential planets pass across them.

Kepler has produced an unprecedented data set for exoplanet hunting. Now in its second "K2" mission it looks for exoplanets in unplanned regions of space along the ecliptic.

Regardless, Kepler 90i, third rock though it may be, is too hot to be habitable. This technique is known as machine learning.

Machine learning had not been applied to data acquired by the Kepler telescope until Shallue came up with the idea, he said.

The researchers used TensaFlow, an open source software library produced by Google, and it only took two hours to train the computer model using a regular desktop PC. This process has been inspired by how neurons connect in human brains and transmit signals.

The Kepler telescope is in its twilight years. "I'm sure there are more firsts in the data waiting for people to find them". However, the weakest signals often are missed using these methods. The light signature recorded by Kepler can then be used to calculate the mass and radius of the planet. This is why they trained the computer to look for weak signs in systems whose stars are supposed to be surrounded by different worlds. "The key is to let the computer learn by example rather than by humans inputting specific rules".

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.

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. The only thing they needed is the "right tool or technology to unearth them". "Machine learning really shines in situations where there is so much data that humans can't search it for themselves". They said that it is 30 percent bigger than the Earth.

Will machine learning change astronomy? .

It will be up to more advanced telescopes, like the James Webb Space Telescope targeted for launch in 2019, to study the atmospheres of these distant worlds and sniff out any traces of possible life, Vanderburg noted.

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