An image of the Milky Way Galaxy in Infrared. Image Credit: Spitzer Space Telescope.

Artificial Intelligence Helped Create The Largest Three-Dimensional Map of The Cosmos

The new catalog doubles the area surveyed compared to the previous largest map of the universe.


Artificial intelligence has helped astronomers create the largest Three-Dimensional map of the Cosmos.

There’s nothing like taking time off to go somewhere where light pollution is minimal, allowing you to observe, among other things, the Milky Way Galaxy. However, the unaided eye can only see so much.


I’ve been learning the “secrets” of astrophotography for the last few months. In this process, I have learned much about our planet, the stars, galaxies, and the unfathomable number of stars we cannot see with the unaided eye. My camera produces some stunning views of the cosmos, and when paired with my telescope, the results are awestriking. But this is just with simple tools most of us can acquire.

However, experts use better “telescopes” and cameras when looking at the stars. Their quest to understand the cosmos is of great importance. Humans have made fantastic progress in cataloging the solar system, our immediate cosmic neighborhood, the Milky Way Galaxy, and the universe.

A team of scientists from the University of Hawaii at the Manoa Institute for Astronomy (IfA) has produced the most extensive catalog of 3D astronomical images of stars, galaxies, and quasars in a massive leap toward understanding the cosmos.

With the help of data from the panoramic telescope and the UH or Pan-STARRS1 (PS1) rapid response system, researchers could obtain the largest deep multi-color optical survey, covering three-quarters of the sky. In other words, it is massive.

 Largest Three-Dimensional Map of The Cosmos

How massive, you ask? According to astronomers, the new tools have allowed them to go through a humongous cosmic catalog and identify which of the 3 billion objects are stars, galaxies, and quasars. In addition, computational algorithms have also allowed scientists to obtain the distances to distant galaxies in the universe. In other words, what scientists obtained is a total of approximately 300 gigabytes of data.


This can be accessed by scientists and users worldwide, allowing them to consult the catalog through the MAST CasJobs SQL interface or download the entire collection as a machine-readable table.

Astronomers took publicly available spectroscopic measurements that provide definitive object classifications and distances and sent them to an artificial intelligence algorithm that helped get the job done; it has been revealed.

Astronomers stress that the AI process was vital in helping the team figure out how to accurately determine the same properties from various measurements of object colors and sizes.

Artificial intelligence at work

This artificial intelligence learning approach with a “feedback neural network” achieved an overall ranking accuracy of 98.1% for galaxies, 97.8% for stars, and 96.6% for quasars.

Estimates of the galaxy’s distance are nearly 3% accurate. This means that AI has allowed scientists to understand better what the sky is like and what the objects represent.

Utilizing a state-of-the-art optimization algorithm, we leveraged the spectroscopic training set of almost 4 million light sources to predict source types and galaxy distances to teach the neural network. Simultaneously, correcting for light extinction by dust in the Milky Way,” explained Rover Beck, the study’s lead author.

The largest map of the universe is a true wonder, proving that new tools, such as AI, can help scientists better explore the cosmos. Previously, the Sloan Digital Sky Survey (SDSS) created the largest cosmic chart, covering one-third of the sky. The new catalog is so extensive that it doubles the area surveyed. Furthermore, the new cosmic chart has more accurate statistics with specific regions of the sky that the SDSS missed.


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Written by Ivan Petricevic

I've been writing passionately about ancient civilizations, history, alien life, and various other subjects for more than eight years. You may have seen me appear on Discovery Channel's What On Earth series, History Channel's Ancient Aliens, and Gaia's Ancient Civilizations among others.

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