Using Yale University’s supercomputers, a team of astronomers has found for the first time that galaxies in denser environments in the universe are up to 25% larger than those in less dense regions. The discovery comes from an extensive catalog of shapes and sizes of 8 million galaxies previously developed by the researchers, providing comprehensive insights into the structure of galaxies and their relationship to the environments they live in.
The researchers say the discovery may also provide a useful new tool for analyzing large data sets from the next generation of astronomical surveys. “This is an important step toward resolving decades of conflicting results on this subject,” said Aritra Ghosh, a former Yale graduate student who is now a LSST-DA Catalyst postdoctoral fellow at the University of Washington and lead author of the new study, in The Astrophysical Journal.
Ghosh is also a visiting scholar at Yale. This new discovery was made possible by the Galactic Morphology Posterior Estimation Network (GaMPEN), a machine learning tool that the research team developed specifically to rapidly process large amounts of astronomical imaging data. GaMPEN also estimates the uncertainty in the structural parameters of the galaxies it predicts. In this respect, it is about 60% more accurate than state-of-the-art alternatives currently used by astronomers, the researchers said.
GaMPEN can determine the structure of a single galaxy in less than one millisecond. Using this tool, the researchers created a catalog of the shapes and sizes of 8 million galaxies found in the Hyper Suprime-Cam Subaru Strategic Program, a 1,400-square-degree sky survey conducted by the Subaru Telescope in Hawaii. The research was published in a 2023 study in the Astrophysical Journal. “We make all our machine learning models and catalogs publicly available,” Ghosh said, adding, “This is an invaluable asset because we know that the structure of galaxies is closely related to various physical properties, such as the velocities of galaxies and their surroundings.
How stars form, the presence and activity of supermassive black holes, and the environment of galaxies.” “Our machine learning approach is ideally suited to today’s vast surveys, and our first paper was unique in providing quantitative measurements and uncertainties, not to mention an analysis of 8 million galaxies,” added Meg Arie, the Israel Munson Professor of Physics and Astronomy. A professor in the Yale School of Letters and Sciences and a co-author on both studies. Arie, director of the Yale Center for Astronomy and Astrophysics, was Ghosh’s doctoral advisor.
The team’s new study uses GaMPEN to answer complex, essential questions about how galaxies form and evolve. The study, which focused on a subset of 3 million super-primary cam galaxies, found that galaxies in denser parts of the universe are up to 25% larger than galaxies of similar mass and shape in less dense regions. “This is possible because our sample is 100 to 10,000 times larger than previous studies and includes much fainter galaxies than previous studies,” Ghosh said.
“We show that while existing theoretical frameworks can explain some of the observed correlations, there is no single unified framework that can explain all of our results.” The researchers say the discovery is also important because the structure of a galaxy is an indication of the distribution of baryonic matter (protons, neutrons, and other visible matter), and the ambient density of a galaxy is influenced by the distribution of dark matter halos, where galaxies live. “Galaxies evolve over time, and their properties are determined by their mass, size, and other variables,” Urey said.
“By analyzing very large samples sorted by these variables, we were able to confirm that galaxy size increases with surrounding density, something that was not evident in smaller studies.” The researchers also said they benefited greatly from GRACE, a networked cluster of Yale computers run by the Yale Research Computing Center and named after the late Yale computer science pioneer and U.S. Navy Rear Admiral Grace Murray Hopper. “This work was done entirely in collaboration with Grace and would not have been possible without her,” Ghosh said.
source:DOI: 10.3847/1538-4357/ad596f