AI Deep Neural Networks find 1200 potential gravitational lenses at Berkeley lab

A research team of scientists from the Berkeley lab has used Artificial Intelligence(AI) to discover about 1200 possible gravitational lenses. According to phys.org if this count is accurate, this could double the number of existing gravitational lenses. Read more to find out what gravitational lenses are.  

Gravitational Lenses

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So what exactly are these gravitational lenses? When light emitted by stars from distant galaxies pass massive objects in the universe, like a cluster of star systems or a bunch of galaxies, the light gets bent or distorted due to the incredibly powerful gravitational force. This strange space phenomenon is called gravitational lensing. Strong gravitational lensing can lead to multiple images of the same galaxies forming in space as the light from various sources is being pulled in. On the other hand, weak gravitational lensing results in galaxies appearing distorted, stretched or magnified. Gravitational lenses are notoriously difficult to find. 

Dark Matter

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These gravitational lenses are important for astrophysicists to study because they help scientists explore the nature of dark matter and its gravitational effects. Dark matter is not visible to the naked eye and it is theorised that dark matter constitutes most of the unknown matter in the universe. Dark matter can only be observed by observing it's gravitational effects on visible matter. Scientists can study these gravitational lenses and theoretically study the existence of dark matter in the universe. 

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These new gravitational lenses have been discovered using a form of Artificial Intelligence, known as deep residual networks. All these potential lenses are considered to be strong gravitational lenses, which means their effects will be clearly observable. "I really thought it would be many years before anyone would find this many gravitational lenses," David Schlegel said, one of the physicists who participated in the study, said, "It's just amazing to know that you're seeing, very clearly, space itself being warped by a massive object." Previously, David Schlegel had also participated in a study that turned up 335 new strong lensing candidates.

According to phys.org, the researchers had used 632 observed gravitational lenses and potential lens candidates, along with 21,000 non-lenses to train the deep neural network AI, that was used to make the discovery. This sample set of lenses were taken from two surveys, DECaLS and DES. It was expected about one in 10,000 massive galaxies was expected to contain a strong gravitational lens. The scientists used computing resources of the Berkeley Lab’s National Energy Research Scientific Computer Center (NERSC) for their data analysis.

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