Using artificial intelligence, an international team analyzed the chemical composition of extremely metal-poor stars, finding that the first stars in the Universe were likely born in groups rather than individually. This method will be applied to future observations to better understand the early Un
An international team has used artificial intelligence to analyze the chemical abundances of old stars and found indications that the very first stars in the Universe were born in groups rather than as isolated single stars. Now the team hopes to apply this method to new data from on-going and planned observation surveys to better understand the early days of the Universe., the only elements in the Universe where hydrogen, helium, and lithium.
In this study, a team including members from the University of Tokyo/Kavli IPMU, National Astronomical Observatory of Japan, and University of Hertfordshire took a novel approach of using artificial intelligence to interpret elemental abundances in over 450 extremely metal-poor stars observed by telescopes including the Subaru Telescope. They found that 68% of the observed extremely metal-poor stars have a chemical fingerprint that is consistent with enrichment by multiple previous supernovae.
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