Artificial Intelligence Revolutionising Cosmology: Understanding the Universe's Core Settings
Artificial Intelligence Transforming Data Analysis in Cosmology
Artificial intelligence (AI) is making waves beyond traditional applications. 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) have leveraged AI to calculate five cosmological parameters that characterise the universe, enhancing our knowledge of its structure and evolution.
Unveiling the Universe's Settings
The five cosmological parameters define the universe's 'settings,' dictating its behaviour at large scales. According to Liam Parker, an astronomer at CCA and co-author of the study, these parameters function like the universe's operating instructions. By applying AI to data from over 100,000 galaxies observed in the Sloan Digital Sky Survey (SDSS), the research team achieved exceptional accuracy.
Maximising Data Efficiency
AI enabled the extraction of detailed insights from SDSS data, overcoming limitations of traditional analysis methods. Co-author Shirley Ho, another astronomer at CCA, emphasised the cost savings associated with this approach, as traditional surveys can be prohibitively expensive.
Training AI for Precision
The researchers trained the AI model using 2,000 simulated universes under varied cosmological settings. This training set included challenges like atmospheric distortion to ensure the AI's reliability. The results were impressive, as the AI halved the uncertainty in measuring the universe's 'clumpiness,' comparable to conducting traditional analyses with quadruple the data volume.
Impact on Cosmic Mysteries
The incorporation of AI in cosmology addresses significant cosmic questions, including the Hubble tension, which involves discrepancies in different Hubble constant estimates. Improved precision could resolve this issue, furthering our comprehension of the universe. As new surveys like the European Euclid survey emerge, the AI-powered techniques from CCA are poised to extract maximum value from expansive datasets.
This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.