Machine Learning Tackles Spacetime

In a breathtaking reveal last year, the Event Horizon Telescope gave the world its first view of a black hole’s shadow. But what exactly goes on inside a black hole? General relativity would tell us that a black hole is a singularity in spacetime, a mathematical feature at odds with the fuzziness of quantum mechanics. If scientists want to understand what’s happening inside a black hole, they will have to unify the two theories. So far, the most popular formulation of a quantum theory of gravity has been in terms of string theory. A major sticking point, however, has been a prohibitively complex calculation of a quantum-mechanical wave function. New work by Xizhi Han and Sean Hartnoll from Stanford University, California, demonstrates that neural networks—much like those used to generate realistic images of faces—may make this calculation much easier to do [1]. Their results open up a new way to explore the quantum properties of gravity with a computational approach, allowing theorists to “experiment" with gravity.