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Astronomers Apply AI to Discover and Classify Galaxies

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A research group of astronomers, with most coming from the National Astronomical Observatory of Japan (NAOJ), are now applying artificial intelligence (AI) to ultra-wide field-of-view images of the universe captured by the Subaru Telescope. The group has managed to achieve a high accuracy rate for finding and classifying spiral galaxies in those images.

This technique is used along with citizen science, and the two are expected to lead to more discoveries in the future.

The researchers applied a deep-learning technique in order to classify galaxies in a large dataset of images which were obtained through the Subaru Telescope. Due to its extremely high sensitivity, the telescope has detected around 560,000 galaxies in the images. 

The Subaru Telescope is important since the task of identifying that many galaxies by human eye for morphological classification would be nearly impossible. Thanks to the AI, the team was able to process the information without the need of human intervention.

The work was published in Monthly Notices of the Royal Astronomical Society.

Automated Processing Techniques

Starting in 2012, the world has seen a rapid development of automated processing techniques for extraction and judgement of features with deep-learning algorithms. These are often much more accurate than humans and are present in autonomous vehicles, security cameras and various other applications.

Dr. Ken-ichi Tadaki is a Project Assistant Professor at NAOJ. He is responsible for the idea that if AI is capable of classifying images of cats and dogs, there is no reason it should not be able to identify and distinguish “galaxies with spiral patterns” from “galaxies without spiral patterns.”

Through the use of training data prepared by humans, the AI was capable of successfully classifying the galaxy morphologies with an accuracy rate of 97.5%. After being applied to the full data set, the AI could identify spirals in about 80,000 galaxies. 

Classifying Galaxies with Artificial Intelligence

Citizen-Science Project

Since the new technique was effective at identifying the galaxies, the group can now use it to classify galaxies into more detailed classes. This will be done by training the AI on many galaxies which have been classified by humans. 

NAOJ runs a newly created citizen-science project called “GALAXY CRUISE,” which relies on citizens examining galaxy images that were taken with the Subaru Telescope. The citizens then look for features that suggest the galaxy is either merging or colliding with another galaxy.

Associate Professor Masayuki Tanaka is the advisor of “GALAXY CRUISE,” and he strongly believes in the study of galaxies through artificial intelligence.

“The Subaru Strategic Program is serious Big Data containing an almost countless number of galaxies. Scientifically, it is very interesting to tackle such big data with a collaboration of citizen astronomers and machines,” Tanaka says. “By employing deep-learning on top of the classifications made by citizen scientists in GALAXY CRUISE, chances are, we can find a great number of colliding and merging galaxies.”

The new technique created by the group of astronomers has big implications for the field. It is another example of how artificial intelligence will not only change life on our planet, but how it will also help us expand our knowledge beyond.


Alex McFarland is an AI journalist and writer exploring the latest developments in artificial intelligence. He has collaborated with numerous AI startups and publications worldwide.