Artificial Intelligence Analyses Distortions In Spacetime A Whopping 10 Million Times Faster

Artificial intelligence isn't just good for customer service chatbots and personal assistants on your mobile, advances in the field are also helping to revolutionise scientific research. Scientists from the Department of Energy's SLAC National Accelerator Laboratory and Stanford University have shown that a form of AI known as neural networks can accurately analyse complex distortions in spacetime a whopping ten million times faster than traditional methods. "Analyses that typically take weeks to months to complete, that require the input of experts and that are computationally demanding, can be done by neural nets within a fraction of a second, in a fully automated way and, in principle, on a cell phone's computer chip," said postdoctoral fellow Laurence Perreault Levasseur, a co-author of a study published in Nature. KIPAC scientists have for the first time used artificial neural networks to analyze complex distortions in spacetime, called gravitational lenses, demonstrating that the method is 10 million times faster than traditional analyses. The team at the Kavli Institute for Particle Astrophysics and Cosmology, a joint institute of SLAC and Stanford, used the neural networks to look at images of strong gravitational lensing, where a picture of a far-flung galaxy is multiplied and distorted by the gravity of a massive object that's closer to us, such as a galaxy cluster.