Researchers have developed a new artificial intelligence powered simulation that could significantly improve our understanding of how the universe creates many of its heaviest elements. Created by an international team at GSI/FAIR, the machine learning model allows scientists to simulate the complex nuclear reactions that occur during neutron star mergers and other violent stellar events far more efficiently than before. Their findings were published in the journal Physical Review D.
AI Improves Simulations of Heavy Element Formation
Many of the chemical elements found throughout the universe are forged during extreme cosmic events, including supernova explosions and neutron star mergers. These enormous explosions generate the energy needed to produce heavy atomic nuclei through a process known as rapid neutron capture, or the r-process.
During the r-process, atomic nuclei rapidly absorb free neutrons. Some of those neutrons then transform into protons, allowing the nuclei to grow larger and eventually form many of the heavy elements found in nature.
Simulating these reactions is one of the biggest challenges in nuclear astrophysics because the calculations require tremendous computing power.
