A supercomputer is helping astronomers solve a long-standing question about the size of galaxies and the environments they inhabit.
A team of astronomers using a supercomputer from Yale University has been able to determine this for the first time. Galaxies In the densest environments, they are 25% larger than their counterparts in the less dense regions of the universe.
This discovery, which comes from scientists’ previous compilation of a massive catalog of the shapes and sizes of 8 million galaxies, provides a comprehensive look at the relationship between a galaxy’s structure and the environment in which it exists.
The discovery could be a useful new tool for analyzing large data sets for the next generation of astronomical research, scientists say.
This is an important step in resolving decades of conflicting findings on this subject. “We are excited to be working with this new study,” said Arista Ghosh, a former Yale PhD student who is currently an LSST-DA Catalyst Fellow at the University of Washington and lead author of the new study. Published In the Astrophysical Journal.
The new discoveries were made possible by the Galaxy Morphology Back-Estimation Network (GaMPEN), a machine learning tool developed by the research team specifically to quickly process large amounts of astronomical imaging data. GaMPEN also estimates uncertainties in the structural parameters of the galaxies it predicts. According to the scientists, it is about 60 percent more accurate in this regard than the state-of-the-art alternative solutions currently used by astronomers.
GaMPEN can determine the structure of a single galaxy in less than a millisecond.
Using this tool, scientists created a catalog of the shapes and sizes of 8 million galaxies in it. Hyper Supreme Cam Subaru Strategic ProgramA 1,400-square-degree survey of the sky was taken. Subaru telescope In Hawaii. This work remained. Published In the Astrophysical Journal in 2023.
We make all of our machine learning models and catalogs publicly available. Ghosh said.This is a very valuable method because the structure of galaxies is closely related to a wide range of physical properties of the galaxy and its surroundings, such as the rate of star formation, their presence and activity. supermassive black holes And the galactic environment.
Our machine learning approach is ideally suited for today’s massive research, and our first work was unique in providing quantitative measurements and uncertainties, not to mention analyzing 8 million stars. “These are the kinds of things that are happening,” said Meg Ury, the Israel Musson Professor of Physics and Astronomy in the Yale School of Arts and Sciences and a co-author of both studies. Ury, director of the Yale Center for Astronomy and Astrophysics, was Ghosh’s doctoral advisor.
The team’s new study uses GaMPEN to begin to answer complex and important questions about galaxy formation and evolution.
The study, which focused on a subset of 3 million HSC galaxies, found that galaxies in the densest parts of the universe are up to 25% larger than galaxies of similar mass and shape in less dense regions.
We can do this because our sample is 100 to 10,000 times larger than all previous studies and includes much fainter galaxies than previous studies have been able to explain. Ghosh said. We have shown that although existing theoretical frameworks can explain some of the observed associations, no single unified framework can explain all of our findings.
The discovery is also important because the galaxy’s structure is an indicator of decay, the scientists said. Baryonic matter (protons, neutrons, and other visible matter), while the density of galaxies in the environment is affected by the distribution of dark matter halos in which galaxies live.
Galaxies evolve over time, and their properties depend on mass, size, and other variables. Uri said. By analyzing very large samples, divided by these variables, we were able to detect an increase in galaxy size with environmental density – something that was not evident in smaller studies.
development:
Agnieszka Novak
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Source: Yale University
In the illustration: Galactic structures. Source: Shy Genel and Illustris Collaboration
