Jan. 9 (UPI) -- Scientists have developed new computer algorithms for identifying galactic mergers.
The technology allows scientists to scan galactic surveys for the stellar velocities and galactic structures most likely to result from the merging of two galaxies.
By finding and studying more galaxy mergers, scientists hope to better understand how giant galaxies like the Milky Way form and evolve over time.
"The goal is to build a bigger sample of merging galaxies than ever before," Rebecca Nevin, a graduate student at the University of Colorado, said in a news release.
To build the new technology, Nevin and her research partners simulated the many ways a pair of galaxies might collide and merge, revealing a range of possible stellar effects.
Until now, scientists have relied on human eyes to identify galactic mergers, but humans miss lots of mergers.
"These simulated galaxy mergers allow us to follow billions of years of evolution directly, whereas observations of real galaxies are limited to single moments in time," said Laura Blecha, an assistant professor at the University of Florida.
Researchers used the results of their simulations to train a machine learning program to pick out the signatures of potential galactic mergers. When scientists fed the algorithms images collected by the Sloan Digital Sky Survey, the program successfully identified 80 percent of the galactic mergers.
Scientists presented the new technology to attendees of this week's Meeting of the American Astronomical Society in Seattle.