Denser Environments Cultivate Larger Galaxies

Eddie Gonzales Jr. – MessageToEagle.com – Galaxies exist in varying environments, from densely populated regions to isolated universe areas with few or no neighboring galaxies.

A new study has found that galaxies with more neighbors tend to be larger than their counterparts, which have a similar shape and mass but reside in less dense environments.

Galaxies Are Larger In Denser Environments - A Study

Images of galaxies of a variety of shapes and sizes. New research shows that galaxies with more nearby neighbors tend to be larger.NAOJ/NASA/ESA/CSA

Now, researchers at the University of Washington, Yale University, the Leibniz Institute for Astrophysics Potsdam in Germany, and Waseda University in Japan report that galaxies found in denser regions of the universe are as much as 25% larger than isolated galaxies.

The team used a new machine-learning tool to analyze millions of galaxies, helps resolve a long-standing debate among astrophysicists over the relationship between a galaxy’s size and its environment.

“Current theories of galaxy formation and evolution cannot adequately explain the finding that clustered galaxies are larger than their identical counterparts in less dense regions of the universe,” said lead author Aritra Ghosh, a UW postdoctoral researcher in astronomy and an LSST-DA Catalyst Fellow with the UW’s DiRAC Institute.

“That’s one of the most interesting things about astrophysics. Sometimes what the theories predict we should find and what a survey actually finds are not in agreement, and so we go back and try to modify existing theories to better explain the observations.”

Past studies found cluster galaxies smaller than isolated ones, while others concluded the opposite.

Galaxies Are Larger In Denser Environments - A Study

Image of Abell 2218, a dense galactic cluster approximately 2 billion light years from Earth.NASA/ESA/Johan Richard

In this new study, Ghosh and his colleagues utilized a survey of millions of galaxies conducted using the Subaru Telescope in Hawaii. This endeavor, known as the Hyper Suprime-Cam Subaru Strategic Program, took high-quality images of each galaxy.

The team chose 3 million galaxies with the best data and used machine learning to measure their sizes. They then placed a 30-million-light-year radius circle around each galaxy to represent its immediate surroundings.

The question was: How many neighboring galaxies lie within that circle?

The study revealed that galaxies with more neighbors were generally larger. This could be due to several factors: dense galaxy clusters may form larger galaxies initially, merge more efficiently, or be influenced by dark matter halos’ gravitational pull, which affects galaxy evolution.

“Theoretical astrophysicists will have to perform more comprehensive studies using simulations to conclusively establish why galaxies with more neighbors tend to be larger,” said Ghosh. “For now, the best we can say is that we’re confident that this relationship between galaxy environment and galaxy size exists.”

The team reached a clear conclusion using the Hyper Suprime-Cam Subaru Strategic Program’s large dataset. Additionally, their new machine learning tool determined galaxy sizes while accounting for measurement uncertainties.

“One important lesson we had learned prior to this study is that settling this question doesn’t just require surveying large numbers of galaxies. You also need careful statistical analysis. A part of that comes from machine learning tools that can accurately quantify the degree of uncertainty in our measurements of galaxy properties.” said Ghosh in a press release.

The machine learning tool that they used is called GaMPEN — or Galaxy Morphology Posterior Estimation Network, which freely available online.

“Very soon, large datasets will be the norm in astronomy,” said Ghosh. “This study is a perfect demonstration of what you can do with them — when you have the right tools.”

Original of this press release – here

Paper

Written by Eddie Gonzales  Jr. – MessageToEagle.com Staff Writer