This article was originally published in The conversation. The publication contributed the article to Space.com’s Expert Voices: Op-Ed & Insights.
The famous first image of a black hole just got twice as sharp. A research team used artificial intelligence to dramatically improve its first image from 2019, which now shows the black hole at the center of the M87 galaxy as darker and larger than the first image depicted.
I am an astronomer who studies and has written about cosmology, black holes and exoplanets. Astronomers have been using artificial intelligence for decades. In fact, in 1990 astronomers from the University of Arizona, where I am a professor, were among the first to use a type of AI called a neural network to study the shapes of galaxies.
Since then, artificial intelligence has spread to all areas of astronomy. As technology has become more powerful, AI algorithms have begun to help astronomers tame massive data sets and discover new knowledge about the universe.
Better telescopes, more data
For as long as astronomy has been a science, it has involved trying to understand the many objects in the night sky. It was relatively simple when the only tool was the naked eye or a simple telescope, and all that could be seen were a few thousand stars and a handful of planets.
A hundred years ago, Edwin Hubble used newly built telescopes to show that the universe is filled with not just stars and gas clouds, but countless galaxies. As telescopes have continued to improve, the sheer number of celestial bodies humans can see and the amount of data astronomers have to sort through has also grown exponentially.
For example, the soon-to-be-completed Vera Rubin Observatory in Chile will render images so large that it would take 1,500 high-definition television screens to view each one in its entirety. Over 10 years, it is expected to generate 0.5 exabytes of data—about 50,000 times the amount of information stored in all the books in the Library of Congress.
There are 20 telescopes with mirrors larger than 20 feet (6 meters) in diameter. AI algorithms are the only way astronomers could ever hope to work through all the data available to them today. There are a number of ways in which AI proves useful in processing this data.
Related: The 10 largest telescopes on Earth
Astronomy often involves looking for needles in a haystack. About 99% of the pixels in an astronomical image contain background radiation, light from other sources or the blackness of space – only 1% have the subtle shapes of faint galaxies.
AI algorithms—especially neural networks that use many interconnected nodes and are able to learn to recognize patterns—are perfectly suited to picking out the patterns of galaxies. Astronomers began using neural networks to classify galaxies in the early 2010s. Now the algorithms are so efficient that they can classify galaxies with 98% accuracy.
This story has been repeated in other areas of astronomy. Astronomers working on SETI, the Search for Extraterrestrial Intelligence, use radio telescopes to look for signals from distant civilizations. Early radio astronomers scanned charts by eye to look for anomalies that could not be explained. Recently, researchers used 150,000 personal computers and 1.8 million citizen scientists to look for artificial radio signals. Now researchers are using AI to sift through volumes of data much faster and more thoroughly than humans can. This has allowed SETI’s efforts to cover more ground while reducing the number of false positives.
Another example is the search for exoplanets. Astronomers discovered most of the 5,300 known exoplanets by measuring a decrease in the amount of light coming from a star when a planet passes in front of it. AI tools can now pick out the signs of an exoplanet with 96% accuracy.
Make new discoveries
AI has proven to be excellent at identifying known objects — like galaxies or exoplanets — that astronomers tell it to look for. But it is also quite powerful for finding objects or phenomena that are theorized but have not yet been discovered in the real world.
Teams have used this approach to discover new exoplanets, learn about the progenitor stars that led to the formation and growth of the Milky Way, and predict the signatures of new types of gravitational waves.
To do this, astronomers first use AI to convert theoretical models into observational signatures – including realistic noise levels. They then use machine learning to sharpen the AI’s ability to detect the predicted phenomena.
Finally, radio astronomers have also used AI algorithms to sift through signals that do not correspond to known phenomena. Recently, a team from South Africa found a unique object that may be a remnant of the explosive merger of two supermassive black holes. If this turns out to be true, the data will allow a new test of general relativity – Albert Einstein’s description of space-time.
Making predictions and closing gaps
As in many areas of life recently, generative artificial intelligence and large language models like ChatGPT are also making waves in the world of astronomy.
The team that created the first image of a black hole in 2019 used a generative AI to produce its new image. To do so, it first taught an AI how to recognize black holes by feeding it simulations of many kinds of black holes. The team then used the AI model it had built to fill in gaps in the vast amount of data collected by the radio telescopes on the black hole M87.
Using this simulated data, the team was able to create a new image that is twice as sharp as the original and is fully consistent with the predictions of general relativity.
Astronomers are also turning to artificial intelligence to help tame the complexities of modern research. A team from the Harvard-Smithsonian Center for Astrophysics created a language model called astroBERT to read and organize 15 million scientific articles about astronomy. Another team, based at NASA, has even proposed using AI to prioritize astronomy projects, a process astronomers engage in every 10 years.
As AI has developed, it has become an important tool for astronomers. As telescopes get better, as data sets get bigger, and as artificial intelligence continues to improve, it’s likely that this technology will play a central role in future discoveries about the universe.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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