Artificial Intelligence Helps Astronomers Locate Fast Radio Bursts

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Fast radio bursts were registered at a distance of three billion light years from Earth.

To understand the new fast radio bursts better, the Breakthrough Listen team at the SETI Research Center at University of California, Berkeley observed FRB 121102 on August 26, 2017.

Fast radio bursts are among the most mysterious occurrences in the Universe, and a few have also speculated that they may originate from alien technology.

Theories range from highly magnetised neutron stars, blasted by gas streams near to a supermassive black hole, to suggestions that the burst properties are consistent with signatures of technology developed by an advanced civilisation.

By Geremia at English Wikipedia [Public domain], via Wikimedia CommonsBreakthrough Listen, a program that is looking for aliens throughout the universe, has detected 72 new fast radio bursts thanks to an applied machine learning algorithm.

Andrew Siemion, the director of the Berkeley SETI Research Center, said in a UC Berkeley news item that the successful application of machine learning could lead to more breakthroughs. While most FRBs are detected only during a single outburst, the fast radio bursts of 121102 repeat themselves, making it the only source that emits repeated bursts, including 21 detected bursts from last year's Green Bank Telescope (GBT) in West Virginia by Breakthrough Listen. The fast radio bursts were picked out from a data set that had already been analyzed by astronomers. The 21 fast radio bursts were all seen within one hour, which suggests that whatever the source of FRB 121102 is, it demonstrated a period of excessive activity.

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This brings the total number of detected bursts from FRB 121102 to around 300 since it was discovered in 2012, researchers said.

A group of scientists who worked on the algorithm that is used the methods used and IT companies to optimize search results and image classification. These new bursts were missed by conventional search methods, and are helping to answer questions about the origin of FRB 121102. They trained an algorithm is named a convolutional neural community to glimpse bursts came upon by the classical search technique passe by Gajjar and collaborators, after which voice it free on the dataset to get bursts that the classical technique missed.

Researchers have since detected many more FRBs, but their origins remain a mystery to this day. "We hope our success may inspire other serious endeavours in applying machine learning to radio astronomy".

The results have helped put new constraints on the periodicity of the pulses from FRB 121102, suggesting that the pulses are not received with a regular pattern, at least if the period of that pattern is longer than about 10 milliseconds.

Gerry Zhang, a Ph.D. student at the University of California, Berkeley, and co-author of the study concludes that the project is essential in understanding the Universe, even if these FRBs turn out not to be "signatures of extraterrestrial technology". They used the Breakthrough Listen digital instrumentation at the GBT. 2018) accepted for publication in the Astrophysical Journal.

For a decade, astronomers relish puzzled over ephemeral however extremely noteworthy radio bursts from home.

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