Using Machine Learning to Accurately Simulate 100 Million Atoms
Researchers from the University of Illinois at Urbana-Champaign have recently demonstrated the ability to accurately simulate 100 million atoms using machine learning—a feat that used to be considered impossible. This groundbreaking development has the potential to revolutionize the field of materials science and engineering, as it allows researchers to study large-scale physical phenomena at unprecedented levels of detail and accuracy. The research team used a combination of classical physics and machine learning algorithms to simulate the behavior of a 100 million atom system over time. By utilizing machine learning, they were able to reduce the computational time by two orders of magnitude compared to traditional methods. The results of the study show that machine learning is a powerful tool for simulating complex physical phenomena, and demonstrate the potential for this approach to be used in a variety of applications.
source: Next Big Future