A team of Japanese scientists has used artificial intelligence (AI) to uncover mysterious bubble-like structures scattered throughout the Milky Way. These formations, linked to star births and supernova explosions, had previously gone unnoticed due to their subtle nature.
Now, thanks to deep learning models trained on space telescope data, astronomers have a new window into the evolution of our galaxy.
AI Reveals What Human Eyes Have Missed
For years, astronomers have manually analyzed space images to identify Spitzer bubbles, which form around young, massive stars or as remnants of stellar explosions. However, with vast amounts of data streaming in from space telescopes, traditional detection methods have struggled to keep up.
According to the study published in Publications of the Astronomical Society of Japan, to tackle this challenge, researchers from Osaka Metropolitan University developed an AI-powered model designed to scan astronomical images with unprecedented precision.
The system was trained using data from the Spitzer Space Telescope and the James Webb Space Telescope, allowing it to pinpoint hidden bubble-like structures that had escaped previous detection.
The Fingerprints Of Stellar Life Cycles
These cosmic bubbles act as a record of star formation and death. When massive stars form, they release intense radiation and stellar winds, carving out hollow cavities in the surrounding interstellar gas. Similarly, when these stars explode in supernovae, they send shockwaves that push gas outward, creating expanding shell-like structures.
By identifying and mapping these formations, astronomers gain insight into the forces shaping the Milky Way. The study not only helps trace how and where stars are born, but also reveals how supernova explosions impact the structure of galaxies over time.
AI’s Growing Role In Space Exploration
The discovery highlights the expanding role of AI in astronomy. Traditional methods often rely on manual review, but deep learning algorithms can scan massive datasets in a fraction of the time. This means scientists can process thousands of images efficiently, identifying patterns and structures that human eyes might overlook.
“Our results show it is possible to conduct detailed investigations not only of star formation, but also of the effects of explosive events within galaxies,” said graduate student Shimpei Nishimoto, a lead researcher on the project.
His advisor, Professor Toshikazu Onishi, believes AI will continue to transform the study of galaxy evolution. With advancements in machine learning, astronomers may soon uncover even more hidden structures across the universe.
A New Era Of Galactic Discovery
Scientists plan to expand this AI-driven research, applying their models to new telescope data from upcoming missions, including the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope. These powerful observatories will provide even deeper views of the cosmos, allowing AI to uncover more hidden patterns in galactic evolution.
The Milky Way, once thought to be a well-mapped galaxy, continues to surprise astronomers. “In the future, we hope that advancements in AI technology will accelerate the elucidation of the mechanisms of galaxy evolution and star formation.” he added.
