Astronomers from the universities of Groningen, Naples and Bonn are using artificial intelligence to search for rare gravitational lenses in enormous piles of astronomical observations of the universe. They say the method is based on:

… the same artificial intelligence algorithm that Google, Facebook and Tesla have been using in the last years.

The researchers published their method and 56 new gravitational lens candidates in the November, 2017 issue of the peer-reviewed journal Monthly Notices of the Royal Astronomical Society. They said they used what are called convolutional neural networks in their search for gravitational lenses. Their statement explained:

Without the use of artificial intelligence, the hunt for gravitational lenses is difficult. Astronomers must sort thousands of images of the universe. That is one reason gravitational lenses are rare. These objects are a prediction of Einstein’s general relativity theory, which says that mass can bend light. Look back at the image at the top of this post. It looks like a ring around a galaxy, but it’s really a kind of illusion … a massive galaxy in front of a more distant galaxy. The light of the more distant one is bent by the intervening galaxy, to form the ring. This gravitational lensing effect can create multiple images of galaxies, or it can create apparent rings around galaxies, like the one above, called Einstein Rings.

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Astronomers want to study gravitational lenses. They’re an aid to understanding the dark matter thought to pervade our universe. Yet … how to find them? Seeking gravitational lenses among the billions of galaxies in our universe is painstaking, to say the least.

That is why these astronomers worked to train a neural network, using millions of homemade images of gravitational lenses. Then they confronted the network with millions of images from a small patch of the sky. That patch had a surface area of 255 square degrees. That’s just over half a percent of the sky. Their statement told what happened:

Initially, the neural network found 761 gravitational lens candidates. After a visual inspection by the astronomers the sample was downsized to 56. The 56 new lenses still need to be confirmed by telescopes as the Hubble Space Telescope. In addition, the neural network rediscovered two known lenses.

Unfortunately, the researchers said, their neutral network did not see a third known lens. They said it was:

… a small lens and the neural network was not trained for that size yet.

In the future, the researchers said, they want to train their neural network to notice smaller lenses such as the one missed in the initial study and to reject false lenses. The final goal is to completely remove the need for any visual inspection.

Carlo Enrico Petrillo of the University of Groningen, The Netherlands is first author of the new work. He said:

This is the first time a convolutional neural network has been used to find peculiar objects in an astronomical survey. I think it will become the norm since future astronomical surveys will produce an enormous quantity of data which will be necessary to inspect. We don’t have enough astronomers to cope with this.

Bottom line: Astronomers trained a convolutional neural networks – the same kind of artificial intelligence used by Facebook, Tesla and Google – to search for gravitational lenses. They found 56 candidates.

Source: Finding strong gravitational lenses in the Kilo Degree Survey with Convolutional Neural Networks.

Via Astronomie.nl