A research study led by astronomers at the International Centre for Radio Astronomy Research (ICRAR) may have found the explanation for variations in the shapes of galaxies.
By utilizing synthetic intelligence, researchers have actually potentially fixed an enduring concern about the development of galaxies, accelerating their research study procedure.
The researchers have potentially fixed a long-standing question about the advancement of galaxies, utilizing synthetic intelligence (AI) to accelerate their research study.
Since the innovation of the Hubble Sequence, a system for classifying galaxy shapes, in 1926, astronomers have been constantly enhancing our comprehension of galaxy advancement and morphology as our innovation progresses.
By the 1970s, scientists had verified that lone galaxies tend to be spiral-shaped, and those discovered in clusters of galaxies were likely to be smooth and featureless, referred to as elliptical and lenticular (formed like a lens).
A representation of how the EAGLES program classifies galaxy as examined by AI. Credit: ICRAR
Released in the journal Monthly Notices of the Royal Astronomical Society, brand-new research led by astronomers at the International Centre for Radio Astronomy Research (ICRAR) might have discovered the reason for these differences fits.
Lead author Dr. Joel Pfeffer from The University of Western Australia node of ICRAR, stated the research study describes the morphology-density relation– where clustered galaxies appear smoother and more featureless than their solo counterparts.
” Weve discovered there are a few different things going on when we get great deals of galaxies loaded together,” Dr. Pfeffer said.
” The spiral arms on galaxies are so fragile, and as you go to greater densities in the galaxy clusters, spiral nebula start to lose their gas.
” This loss of gas triggers 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 consequences.”
The study utilized the powerful EAGLE simulations to examine a group of galaxies in detail, using an AI algorithm to categorize galaxies by their shape.
The neural network-based algorithm was trained by ICRAR Ph.D. prospect Mitchell Cavanagh and can classify nearly 20,000 galaxies per minute, compressing what would usually take weeks into one hour.
The simulations carefully match what has actually been observed in the Universe, providing scientists the self-confidence to utilize the simulation results to analyze observations of galaxy clusters
The study also identified numerous lenticular galaxies beyond the high-density regions where they are anticipated, with the modeling recommending they were produced by the combining of two galaxies.
Dr. Pfeffer said the work unites various pieces of research study in galactic evolution, to comprehend the morphology-density relation for the very first time.
” There have actually been lots of ideas over time,” he stated. “But this is the first work to truly put all of the pieces of the puzzle together.”
Reference: “The galaxy morphology– density relation in the EAGLE simulation” by Joel Pfeffer, Mitchell K Cavanagh, Kenji Bekki, Warrick J Couch, Michael J Drinkwater, Duncan A Forbes and Bärbel S Koribalski, 16 December 2022, Monthly Notices of the Royal Astronomical Society.DOI: 10.1093/ mnras/stac3466.
