3D View of space
Pan-STARRS helps with image
A team of astronomers unveiled last week the world’s largest three-dimensional map of the universe, breakthrough data that could be used to learn more about the solar system and near-Earth objects.
By using the Panoramic Survey Telescope and Rapid Response System, also known as Pan-STARRS1, on Haleakala, the University of Hawaii at Manoa Institute for Astronomy produced an expansive imaging catalog of stars, galaxies and quasars.
“This beautiful map of the universe provides one example of how the power of the PanSTARRS big data set can be multiplied with artificial intelligence techniques and complementary observations,” said Ken Chambers, Pan-STARRS director and institute associate astronomer. “As Pan-STARRS collects more and more data, we will use machine learning to extract even more information about near-Earth objects, our solar system, our galaxy and our universe.”
Previously, the largest map of the universe was made by the Sloan Digital Sky Survey in New Mexico, which covers only one-third of the sky. The new catalog created by UH doubles the area surveyed, has greater statistics and contains specific areas the Sloan missed, according to a news release last week.
“Utilizing a state-of-the-art optimization algorithm, we leveraged the spectroscopic training set of almost four million light sources to teach the neural network to predict source types and galaxy distances, while at the same time correcting for light extinction by dust in the Milky Way,” said lead study author Robert Beck, also a former cosmology postdoctoral fellow at the institute.
The 3D catalog is now available through the Mikulski Archive for Space Telescopes. It’s about 300 GB in size, and science users can search in the catalog or download the entire collection as a computer-readable table.
According to the news release, astronomers took publicly available measurements and input them into the artificial intelligence algorithm to accurately determine the same properties from various measures of the colors and sizes of the objects.
The AI approach achieved an overall classification accuracy of 98.1 percent for galaxies, 97.8 percent for stars and 96.6 percent for quasars. Galaxy distance estimates are accurate to almost 3 percent.
This is helpful in gathering more information about the universe, such as the Cold Spot, which is an area of the sky with radiation left over from the birth of the universe.
“Already, a preliminary version of this catalog covering a much smaller area, facilitated the discovery of the largest void in the universe, the possible cause of the Cold Spot,” said Istvan Szapudi, institute astronomer and co-author on the study. “The new, more accurate, and larger photometric red shift catalog will be the starting point for many future discoveries.”