To find them, Chen developed a computer algorithm called StarStream, which searches for streams using a physics-based model rather than relying on visual patterns alone, according to the study. The team then applied the method to Gaia data, which from 2014 to 2025 mapped the positions and motions of billions of stars in the Milky Way.
“It turns out that it’s a lot easier to find things when you have a theoretical expectation of what you’re looking for when you have a simple phenomenological picture,” Gnedin said in the statement.
The results also revealed that many streams do not match the classic expectation of thin, well-aligned trails. Instead, the study reports that some of the newfound streams are shorter, wider or even misaligned with their parent clusters’ orbits — suggesting earlier searches may have missed them by focusing only on the most obvious structures.









