Artificial intelligence program CIaRAN can detect galaxies at the deepest levels of space

An artificial intelligence program called CIaRAN, used to identify faces on facebook, can now identify galaxies at the deepest levels of space. The AI bot scans images taken by radio telescopes and can identify over 7 million galaxies.

The program is the product of data specialist Dr. Chen Wu and astronomer Dr. Ivy Wong, both from the University of Western Australia.

According to Wu, the program was developed using “an open source version of Microsoft and Facebook’s object detection software.” Wu explains, however, that CIaRan was completely rewired to recognize galaxies and not people’s faces.

He continues that CIaRan is essentially an AI bot used to identify radio galaxies by targeting blackholes at their centre. More specifically, the AI bot can identify millions of galaxies from their “supermassive black holes” – located at the core of almost all galaxies-  which “emit powerful radio jets.”

“These supermassive black holes occasionally burp out jets that can be seen with a radio telescope,” said Dr. Wong.

“Over time, the jets can stretch a long way from their host galaxies, making it difficult for traditional computer programs to figure out where the galaxy is.”

“That’s what we’re trying to teach ClaRAN to do,” she continues.

Dr Wong further explains that traditional computer algorithms are only able to detect 90 percent of the galaxies.

“That still leaves 10 per cent, or seven million ‘difficult’ galaxies that have to be eyeballed by a human due to the complexity of their extended structures,” Dr Wong said.

“If ClaRAN reduces the number of sources that require visual classification down to one per cent, this means more time for our citizen scientists to spend looking at new types of galaxies,” she continued.

Dr Wu said ClaRAN represents a new paradigmatic shift called “programming 2.0.”

“All you do is set up a huge neural network, give it a ton of data, and let it figure out how to adjust its internal connections in order to generate the expected outcome,” he said.

“The new generation of programmers spend 99 per cent of their time crafting the best quality data sets and then train the AI algorithms to optimise the rest.”

“This is the future of programming,” he adds.

Further, Dr Wong adds that ClaRAN can revolutionize how telescope observations are processed.

“If we can start implementing these more advanced methods for our next generation surveys, we can maximise the science from them,” she said.

“There’s no point using 40-year-old methods on brand new data, because we’re trying to probe further into the Universe than ever before.”

ClaRAN itself is open to the public and available on GitHub.

Just in today, researchers released a paper on ClaRAN in Monthly Notices of the Royal Astronomical Society, published by Oxford University Press.

Source/image credits: Dr. Chen Wu and Dr. Ivy Wong, ICRAR/UWA.