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Artificial intelligence bot trained by researchers to spot black holes and radio galaxies
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Artificial intelligence bot trained by researchers to spot black holes and radio galaxies

Indo Asian News Service • November 1, 2018, 09:41:58 IST
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This means more time for scientists to spend looking at new types of galaxies: Researcher.

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Artificial intelligence bot trained by researchers to spot black holes and radio galaxies

A team of researchers have taught an Artificial Intelligence (AI) programme – that used to recognise faces on Facebook – to identify galaxies in deep space. The AI bot named “ClaRAN” scans images taken by radio telescopes. Its job is to spot radio galaxies – galaxies that emit powerful radio jets from supermassive black holes at their centres. ClaRAN is the brainchild of big data specialist Dr Chen Wu and astronomer Dr Ivy Wong from The University of Western Australia node of the International Centre for Radio Astronomy Research (ICRAR). Black holes are found at the centre of most, if not all, galaxies. [caption id=“attachment_5483431” align=“alignnone” width=“1280”]Representational image. Image courtesy: Sky and Telescope Representational image. Image courtesy: Sky and Telescope[/caption] “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 programmes to figure out where the galaxy is. That’s what we’re trying to teach ClaRAN to do,” she added. “ClaRAN” grew out of an open source version of Microsoft and Facebook’s object detection software, said Dr Wu, adding that the programme was overhauled and trained to recognise galaxies instead of people. ClaRAN itself is an open source and publicly available on Microsoft-owned GitHub. [caption id=“attachment_5483441” align=“alignnone” width=“1280”]ClaRAN identifies patterns that resemble radio galaxies from telescope data. Image credit: ICRAR ClaRAN identifies patterns that resemble radio galaxies from telescope data. Image credit: ICRAR[/caption] Traditional computer algorithms are able to correctly identify 90 percent of the sources. “That still leaves 10 percent, 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 percent, this means more time for our citizen scientists to spend looking at new types of galaxies,” she added in a paper published in the journal Monthly Notices of the Royal Astronomical Society. “ClaRAN” has huge implications for how telescope observations are processed.

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Astronomy artificial intelligence Black holes Telescopes astrophysics Galaxies Supermassive Black Holes SciTech Radio Galaxies
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