AI uncovers the universe's 'settings' with unprecedented precision, and it could help to resolve the Hubble tension

Astrophysicists have used artificial intelligence (AI) to precisely estimate five of the universe's six "settings" with unprecedented precision. The system could one day help researchers crack the mystery of the Hubble tension.

Scientists use six cosmological parameters to describe the large-scale makeup of our universe. These describe the density of its ordinary matter, or baryons; the density of dark matter and dark energy; and the conditions immediately following the Big Bang — including the universe's opacity and clumpiness.

Getting precise estimates of these numbers is important for understanding how our universe began and how it will evolve. But traditional methods typically only estimate these parameters by looking at the way galaxies are spread out over large scales. 

By applying AI to the problem, the researchers were able to extract numbers for the parameters across smaller scales, yielding a result for our universe's matter clumping that had less than half the uncertainty of previous results. The scientists published their findings Aug. 21 in the journal Nature Astronomy.

"Each of these [telescope] surveys costs hundreds of millions to billions of dollars," study co-author Shirley Ho, a group leader at the Flatiron Institute's Center for Computational Astrophysics (CCA) in New York City, said in a statement. "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 researchers trained their AI system on 2,000 models of box-shaped universes, each with different cosmological settings and muddied data to reflect the limitations in real-life observations. This enabled their model to spot patterns in how galaxies looked based upon the alterations made to each universe's settings.

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