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AI Speeds Up Cosmic Element Creation Study
8 Jul
Summary
- New AI model simulates violent stellar events efficiently.
- AI speeds up calculations for heavy element formation.
- RHINE model publicly available for astrophysical research.
International researchers have developed a novel artificial intelligence simulation, dubbed RHINE, designed to significantly advance our comprehension of heavy element formation in the universe. This machine learning model dramatically accelerates the simulation of complex nuclear reactions that occur during extreme cosmic events such as neutron star mergers.
The RHINE system utilizes deep learning to rapidly estimate energy release during these r-process nuclear reactions. This estimation is crucial for understanding how matter is expelled in stellar explosions and influences observable phenomena like kilonovae. Previously, these detailed calculations required immense computational power, often necessitating simplified models.
By training on extensive reference calculations, RHINE can now accurately predict heating rates with a fraction of the previous computational effort. This breakthrough allows for far more detailed simulations, potentially bridging the gap between experiments at facilities like FAIR and astronomical observations of cosmic events. The RHINE source code has been made publicly accessible to foster further research.
