Researchers Unveil Hyper-Realistic Milky Way Simulation Breakthrough

Researchers at the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) in Japan have achieved a groundbreaking milestone in astrophysics by simulating the Milky Way with unprecedented detail. Collaborating with experts from the University of Tokyo and the Universitat de Barcelona, the team created a model that accurately represents more than 100 billion stars over a time span of 10,000 years. This simulation not only incorporates 100 times more stars than previous models, but it was also executed at a speed 100 times faster.

The impressive feat was made possible by harnessing the power of 7 million CPU cores alongside advanced machine learning algorithms and numerical simulations. The resulting model represents a significant advancement in supercomputing and artificial intelligence, providing astronomers with new tools to study stellar and galactic evolution on a grand scale. The research findings were detailed in a paper titled “The First Star-by-star N-body/Hydrodynamics Simulation of Our Galaxy Coupling with a Surrogate Model,” presented at the Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC ’25).

New Techniques Revolutionize Galactic Simulations

Simulating the dynamics of the Milky Way at the level of individual stars has long been a goal for astronomers. Such simulations are crucial for testing theories related to galactic formation, structure, and evolution. Historically, scientists faced challenges in capturing the numerous forces that influence galaxies, including gravity, fluid dynamics, supernovae, element synthesis, and the effects of supermassive black holes (SMBHs). These processes occur across various scales, complicating the simulation efforts.

Until now, the computational power required to model galaxies with this level of complexity was insufficient. The mass limit for current simulations is around one billion solar masses, which represents less than 1% of the stars in the Milky Way. Furthermore, existing supercomputing systems would take approximately 315 hours (over 13 days) to simulate just one million years of galactic evolution— a mere 0.00007% of the Milky Way’s age, estimated at 13.61 billion years. This limitation meant that only large-scale events could be accurately replicated, and simply adding more supercomputer cores did not solve the underlying issues; it often resulted in decreased efficiency and increased energy consumption.

To overcome these obstacles, Hirashima and his team implemented an innovative AI-driven approach. They developed a machine learning surrogate model that utilized high-resolution simulations of supernovae, enabling the model to predict the impact of these explosions on the surrounding gas and dust up to 100,000 years post-explosion. By integrating this surrogate model with physical simulations, the researchers could effectively capture both the overall dynamics of a Milky Way-sized galaxy and smaller-scale stellar phenomena simultaneously.

Efficiency and Future Applications of the Model

The team’s model was rigorously tested using the Fugaku and Miyabi Supercomputer Systems, located at the RIKEN Center for Computational Science and the University of Tokyo, respectively. The results demonstrated that their new method could accurately simulate star resolution in galaxies exceeding 100 billion stars, achieving the remarkable feat of simulating 1 million years of evolution in just 2.78 hours. At this accelerated rate, simulating 1 billion years of galactic history could be accomplished in only 115 days.

These advancements offer astronomers valuable insights into galactic evolution and the formation of the universe. The research not only emphasizes the potential of integrating AI models into complex simulations but also indicates how this approach could be applied beyond astrophysics. Fields such as meteorology, ocean dynamics, and climate science could benefit from similar techniques, enhancing our understanding of both large and small-scale phenomena.

As the scientific community continues to explore the cosmos, this breakthrough serves as a powerful reminder of the possibilities that lie within the intersection of computing and astrophysics. The future of astronomical research is poised for transformation, driven by innovative methodologies and collaborative efforts.