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Analyzing the Insights into Galaxy Evolution and Morphology

A decades-old question regarding the evolution of the galaxy may have been answered by scientists. This helps leverage the power of artificial intelligence (AI) to expedite their research.

A visual representation of AI classifying galaxies based on data from the EAGLES simulation. Image Credit: ICRAR

Right from the time the Hubble Sequence, which categorizes galaxy morphologies, was fabricated in 1926, astronomers have been refining the knowledge of galaxy evolution and morphology as technology progresses.

By the 1970s, scientists had verified that lone galaxies are inclined to be spiral-shaped, and those discovered in clusters of galaxies were probably smooth and featureless, called lenticular (shaped like a lens) and elliptical.

Having been recently reported in the journal Monthly Notices of the Royal Astronomical Society, a new study headed by astronomers at the International Centre for Radio Astronomy Research (ICRAR) might have exposed the cause for such differences in shapes.

The lead author of the study, Dr. Joel Pfeffer from The University of Western Australia node of ICRAR, stated the research describes the “morphology-density relation”—where clustered galaxies appear to be more featureless and smoother compared to their solo counterparts.

We’ve discovered there are a few different things going on when we get lots of galaxies packed together. The spiral arms on galaxies are so fragile, and as you go to higher densities in the galaxy clusters, spiral galaxies start to lose their gas.

Dr. Joel Pfeffer, Study Lead Author, University of Western Australia

Pfeffer added, “This loss of gas causes them to ‘drop’ their spiral arms, transforming into a lenticular shape. Another cause is galaxy mergers, which can see two or more spiral galaxies crashing together to form one large elliptical galaxy in the aftermath.”

The study made use of the strong EAGLE simulations to examine a galaxy group elaborately by making use of an AI algorithm to categorize galaxies by their shape.

The neural network-based algorithm was skilled by ICRAR Ph.D. candidate Mitchell Cavanagh and could classify nearly 20,000 galaxies per minute. This helps compress what would normally take weeks into one hour.

The simulations carefully correspond to what has been noted in the Universe, providing scientists the confidence to utilize the simulation outcome to interpret observations of galaxy clusters.

Furthermore, the study determined various lenticular galaxies’ exteriors of the high-density regions where they are anticipated, with the modeling indicating that they were made by the blending of two galaxies.

Dr. Pfeffer stated the work brings collectively several pieces of research in galactic evolution. This is to comprehend the morphology-density relation initially.

There’s been lots of suggestions over time. But this is the first work to really put all of pieces of the puzzle together.

Mitchell Cavanagh, Ph.D. candidate, International Centre for Radio Astronomy Research

EAGLES Simulation showcases how galaxies could change their shape

Video Credit: ICRAR.

Journal Reference

Pfeffer, J., et al. (2022) The galaxy morphology–density relation in the EAGLE simulation. Monthly Notices of the Royal Astronomical Society.


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