Astrophysicists use AI to precisely calculate universe’s ‘settings’ | Science & Technology

The results were a significant improvement over the values produced by previous methods. Compared to conventional techniques using the same galaxy data, the approach yielded less than half the uncertainty for the parameter describing the clumpiness of the universe’s matter. The AI-powered method also closely agreed with estimates of the cosmological parameters based on observations of other phenomena, such as the universe’s oldest light.

The researchers present their method, the Simulation-Based Inference of Galaxies (or SimBIG), in a series of recent papers, including a new study published August 21 in Nature Astronomy.

Generating tighter constraints on the parameters while using the same data will be crucial to studying everything from the composition of dark matter to the nature of the dark energy driving the universe apart, says study co-author Shirley Ho, a group leader at the Flatiron Institute’s Center for Computational Astrophysics (CCA) in New York City. That’s especially true as new surveys of the cosmos come online over the next few years, she says.

“Each of these surveys costs hundreds of millions to billions of dollars,” Ho says. “The main reason these surveys exist is because we want to understand these cosmological parameters better. So if you think about it in a very practical sense, these parameters are worth tens of millions of dollars each. You want the best analysis you can to extract as much knowledge out of these surveys as possible and push the boundaries of our understanding of the universe.”

The six cosmological parameters describe the amount of ordinary matter, dark matter and dark energy in the…