Artificial intelligence (AI) is making waves beyond the realm of digital assistants and deepfake technology. Astronomers are now harnessing AI to achieve unprecedented precision in understanding the universe's fundamental parameters. Researchers at the Flatiron Institute's Center for Computational Astrophysics (CCA) in New York City have leveraged AI to calculate the five cosmological parameters that characterise the universe, enhancing our knowledge of its structure and evolution.Artificial intelligence (AI) is making waves beyond the realm of digital assistants and deepfake technology. Astronomers are now harnessing AI to achieve unprecedented precision in understanding the universe's fundamental parameters. Researchers at the Flatiron Institute's Center for Computational Astrophysics (CCA) in New York City have leveraged AI to calculate the five cosmological parameters that characterise the universe, enhancing our knowledge of its structure and evolution.
Unveiling the Universe's Settings
The five cosmological parameters in question are crucial as they essentially define the 'settings' of the universe, dictating how it operates on the largest scales. Liam Parker, an astronomer at CCA and a co-author of the study, explained that these parameters are like the universe's operating instructions. To determine these parameters with exceptional accuracy, the research team employed AI to analyse data from over 100,000 galaxies, which were observed as part of the Sloan Digital Sky Survey (SDSS). This survey is instrumental in cosmology as it helps map out the universe by examining how galaxies are distributed across space.
Maximising Data Efficiency
The use of AI allowed the team to extract detailed insights from the SDSS data, a task previously hampered by the sheer volume of information and the limitations of traditional analysis methods. Co-author Shirley Ho, another astronomer at CCA, highlighted the enormous costs associated with such surveys, which can run into billions of dollars. With AI, the team has been able to push the boundaries of what these surveys can reveal, providing a more cost-effective means of extracting valuable knowledge from complex data.
