Artificial Intelligence is now playing a key role in various fields, now in the recent days it is also applied in astronomy and the search for intelligent life in the universe, or SETI.
Researchers from the University of California, Berkeley, used advanced machine learning techniques to discover 72 new fast radio bursts that occurred from a mysterious source approximately 3 billion light years from Earth.
Bright pulses of radio emission mere milliseconds in duration where it is thought to evaluate from distant galaxies which are called fast radio bursts that occur at unclear sources. That ranges high enough for magnetized neutron stars that get blasted by streams from a nearby supermassive black hole, here the properties of the burst remains consistent as it occurs under advanced technology. Breakthrough Listen is also applied to implement the successful machine-learning algorithm which strives to detect new kinds of signals that are coming from extra-terrestrial platforms.
The AI algorithms drag up the radio signals from the incoming data that were recorded over a five-hour period by the Green Bank Telescope in West Virginia. Previous analysis of 400 terabytes of data involved provided standard computer algorithms to recognize 21 bursts during that period that were seen within a time span of 1hour.
UC Berkeley, a Ph.D. student Gerry Zhang and collaborators, explained that we developed a powerful new machine-learning algorithm and reanalyzed the previous data of 2017. “This is the only beginning level of using these powerful methods to find radio transients and we hope that this success may inspire other serious researchers in applying machine learning in the field of radio astronomy.” FRBs individually turn out to be signatures of advanced technology that creates a breakthrough Listen to push the frontiers of a new growing area.