Artificial intelligence algorithm has helped discover 72 new fast radio bursts (Image: Twitter)
Breaking new boundaries in the development of Artificial Intelligence in searching extraterrestrials or aliens in the universe, the University of California has reportedly discovered 72 new fast radio burst from a 'mysterious' source some three billion light years from the planet Earth. The radio bursts are mere milliseconds in duration, thought to originate from far-off galaxies. However, the source of these emissions is still unclear, as per scientists. Fast Radio Bursts are bright pulses of emission originate from distant galaxies reportedly. More FRBs have been spotted during a single outburst.
To observe these FRBs more, the University of California's UC Berkley team took the help of Artificial Intelligence (AI) algorithms to drag the radio signals for a period of five-hour or more. The radio signals data were recorded over a five-hour period on August 26, 2017, by the Green Bank Telescope in West Virginia which was dredged up by AI algorithms.
This has ranged from highly magnetised neutron stars blasted by gas streams from a supermassive black hole. There are reports that advanced civilisation burst properties are consistent with signatures of technology.
"This work is exciting not just because it helps us understand the dynamic behaviour of fast radio bursts in more detail, but also because of the promise it shows for using machine learning to detect signals missed by classical algorithms," said Andrew Siemion, principal investigator for Breakthrough Listen, an initiative led by the University of California, Berkeley in the US to find signs of intelligent life in the universe.
Investigators at ‘Breakthrough Listen’ in order to find new kinds of signals that could be coming from extra-terrestrial civilisations are also applying the successful machine-learning algorithm.
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FRB 121102 source is unique in emitting repeated bursts. This has drawn the attention of many astronomers hoping to pin down the cause and the extreme physics involved in fast radio bursts.
“The source alternates between periods of quiescence and frenzied activity”, said postdoctoral researcher Vishal Gajjar, fron UC Berkeley.
Researches in 2017, reanalysed the data, finding an additional 72 bursts not detected originally. The researchers subsequently developed powerful machine-learning algorithm to study data again.
Researchers now have 300 bursts from FRB 121102 since its discovery in 2012.