Science

Revolutionary AI Technology Surpasses Supercomputers in Simulating Galaxy Evolution

2025-07-03

Author: Jia

AI: The New Frontline in Astrophysics

In a groundbreaking advancement, researchers have harnessed the power of machine learning to dramatically accelerate simulations of galaxy evolution intertwined with supernova explosions. This innovative approach promises to shed light on the primordial origins of our galaxy and the vital elements necessary for life in the Milky Way.

A New Era of Cosmic Understanding

The research, led by Keiya Hirashima from the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences in Japan, in collaboration with the Max Planck Institute for Astrophysics and the Flatiron Institute, aims to crack one of the most perplexing problems in astrophysics: the formation of galaxies.

The Challenge of Galactic Simulations

While we know that events like supernovae are pivotal in shaping galaxy evolution, observing these phenomena in real-time from Earth is impossible. Astrophysicists rely heavily on numerical simulations, which sift through massive datasets from telescopes and instruments measuring the cosmos. These simulations must address intricate factors such as gravity, hydrodynamics, and astrophysical thermochemistry.

Breaking the Bottleneck with AI

One significant hurdle in galaxy simulations is the resolution of temporal data—capturing crucial events like supernova expansion requires incredibly short intervals, often hundreds of years, a feat that traditional supercomputers struggle with. In fact, a typical supercomputer can take one to two years just to simulate a small galaxy at high temporal resolution.

By integrating AI into their modeling, the research team succeeded in bypassing this computational bottleneck, allowing simulations to run approximately four times faster than standard methods. "When we use our AI model, we significantly decrease computation time—from several months to just half a year," notes Hirashima.

Training a Neural Network for Cosmic Predictions

The model trained utilizes a neural network, having learned from 300 simulations of a supernova occurring within a molecular cloud equivalent to a million solar masses. Post-training, the AI can predict various gas properties—density, temperature, and velocity—100,000 years after a supernova event, achieving results that mirror those from traditional supercomputing yet at lightning speed.

A Future of High-Resolution Galactic Simulations

Hirashima points out the potential of this AI-driven framework: "We can now conduct high-resolution simulations of massive galaxies like the Milky Way. This could help us determine the origins of our solar system and identify the elemental building blocks of life." Right now, the research team is already deploying this framework to simulate a Milky Way-sized galaxy, opening doors to unprecedented cosmic discoveries.