This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Using data from the DESI Legacy Imaging Surveys, with help from artificial intelligence, an international team of scientists has discovered 70 new gravitational lenses—rare cosmic alignments that act as natural magnifying glasses. The new lenses further expand one of the largest collections of confirmed lenses to date and will allow scientists to study dark matter, galaxy evolution and the structure of the universe.
In August 2026, the DESI Legacy Imaging Surveys team released the largest 2D map of the universe ever created. The 5.6-trillion-pixel map contains nearly 4 billion celestial objects, including stars, galaxies, black holes and asteroids. This map was created using data from three ground-based sky surveys: The Legacy Surveys map has been 13 years in the making, and regular data releases from the team have enabled scientists to make countless discoveries across a range of subfields in astronomy and astrophysics.
In one such research project, an international team led by Xiaosheng Huang (Santa Clara University and DOE's Lawrence Berkeley National Laboratory) used machine learning to inspect the vast Legacy Surveys data set and identify thousands of new gravitational lens candidates. In an extensive follow-up study published in The Astrophysical Journal Supplement Series, led by Emerald Lin (an undergraduate student at UC Berkeley) and Ivonne Toro Bertolla (a research assistant at NSF NOIRLab and science operations assistant at Las Campanas Observatory), the team spectroscopically confirmed 70 of the candidates, establishing them as true instances of gravitational lensing. A gravitational lens occurs when a massive object such as a galaxy, galaxy cluster or black hole lies directly between Earth and a more distant background object.
The foreground object's gravity bends and magnifies the background light, producing arcs, rings and even multiple images of the same object. These natural telescopes allow astronomers to study objects that would otherwise be too distant or faint to detect. They can magnify galaxies from the early universe, reveal the presence and distribution of invisible dark matter, help improve measurements of the universe's expansion rate and enable the detection of exoplanets—planets orbiting other stars.
"The DESI Legacy Imaging Surveys' deep and wide-field images have provided an unprecedented foundation for discovering new gravitational lenses," says Aleksandar Cikota, an associate scientist at NSF NOIRLab, co-author of the study and PI of the follow-up observing program. "What we're building now is a carefully confirmed sample that researchers can use for years to come." While the Legacy Surveys provided the foundation for discovering these lenses, that foundation was vast. This created both an opportunity and a challenge: Thousands of gravitational lenses were likely waiting to be found, but visually searching for them was impractical.
So the team had to devise a robust and efficient process for scouring the data to identify the lenses buried within them. This is where they turned to artificial intelligence. Using a residual neural network—a form of machine learning designed to recognize subtle patterns in images—the team searched the survey data for the distinctive signatures of gravitational lensing.
Extract — continue reading at the source.
