The Hubble Space Telescope has a big data problem. For more than 35 years, we’ve not only taken some amazing space photos, but collected millions of images.
Together, these images form one of the largest archives in astronomy. Buried inside are rare objects that could change our knowledge of how galaxies grow and how gravity works.
The challenge is not to capture images, but to find unusual images hidden within images.
When humans can’t keep up
Astronomers are very good at noticing strange shapes and patterns. they found that they were distorted galaxy Just scan the image carefully and a strange arc of light will appear.
Sometimes they come across something unexpected by chance. However, the Hubble Archive was too large for that method alone.
Citizen science projects have helped. Volunteers around the world classify galaxies and flag unusual features.
Still, even thousands of dedicated volunteers cannot fully keep up with the modern data deluge. telescope. The skies are being surveyed faster than humans can classify them.
This challenge prompted researchers to try something new.
Teach AI to read Hubble data
Researchers David O’Ryan and Pablo Gomez european space agency I built a neural network – sort of artificial intelligence Learn patterns in your data using a method inspired by the human brain. They named their tool AnomalyMatch.
They trained them to recognize unusual objects such as: jellyfish galaxy and gravity arc. They then published it in the Hubble Legacy Archive.
In just two and a half days, AnomalyMatch sifted through nearly 100 million image clippings. I marked possible oddities and sent it back for expert review.
hundreds of new discoveries
The results were amazing. After personally checking the most promising candidates, the team identified more than 1,300 real-world anomalies.
More than 800 of these had never been recorded in the scientific literature before.
“Hubble Space Telescope archive observations, which now date back 35 years, represent a treasure trove of data from which astrophysical anomalies can be discovered,” said O’Ryan, lead author of the study.
Unusual object revealed
Most of the newly identified objects were galaxies in the process of merging or interacting. when galaxies collidegravity stretches them into strange shapes, pulling out long tails of stars and gas.
These troubling encounters help scientists understand how galaxies grow over time.
The research team also discovered many gravitational lenses. In these star systems, the gravity of foreground galaxies bends space-time, distorting light from distant galaxies behind them.
The result may look like a glowing ring or arc. This lens is not only beautiful; They have allowed astronomers to measure dark matter, allowing them to study galaxies that would otherwise be too dark to see.
New anomaly in Hubble data
Other discoveries include galaxies filled with giant star clumps, jellyfish galaxies trailing gaseous tentacles, and planet-forming disks that resemble hamburgers and butterflies when viewed head-on.
Dozens of objects did not fit into any known categories. These may prove to be particularly important.
“This is a great use of AI to maximize the scientific output of the Hubble Archive,” said study co-author Gomez.
“Discovering so many unusual objects in the Hubble data is an impressive result, even though you might think that many have already been discovered. It also shows how useful this tool is for other large datasets.”
The coming wave of data
Hubble is just the beginning. In 2023, the European Space Agency’s Euclid mission began exploring the billions of galaxies that span a third of the night sky.
NSF-DOE’s Vera C. Rubin Observatory will soon begin a 10-year space-time legacy survey, collecting more than 50 petabytes of images.
NASA’s Nancy Grace Roman Space Telescope is scheduled to launch by May 2027 at the latest, adding even more capabilities.
Each of these projects generates data on a scale that dwarfs human teams. Without smart tools, rare discoveries can slip through the cracks.
Human judgment still required
AI systems like AnomalyMatch are not meant to replace astronomers. They act more like tireless assistants.
They quickly scan everything, flag anything that looks unusual, and leave the final decision to the experts.
A combination of speed and human insight may be the only way to deal with what happens next.
The information was obtained from someone press release Published by the European Space Agency.
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