SETI Breakthrough Listen Initiative data leads to the discovery of 8 previously unknown signals of interest in extraterrestrial search.
Using data from the Search for Extraterrestrial Intelligence (SETI) Breakthrough Listen Initiative, this study revealed eight previously unknown signals of interest; however, these signals have not been caught again in follow-up observations.
Detection of specific radio signals could suggest the presence of technologically advanced life, as artificial signals can be differentiated from natural ones.
For decades, SETI programs have used radio telescopes to monitor the sky for unmistakable artificial signals originating from the stars.
However, interference from human technology makes this search more difficult. This interference may produce false positive identifications, which are hard to remove from huge data sets because of their high volume.
Using more than 480 hours of data from the Robert C. Byrd Green Bank Telescope’s observation of 820 stars, Peter Ma and colleagues describe a selection approach based on machine learning.
The approach analyzed 115 million data points and found around 3 million signals of relevance. Following that, the approach was able to lower this number even more, bringing it down to 20,515 signals, which is almost 100 times fewer than what was found in an earlier analysis of the same dataset.
The team examined all 20,515 signals and found 8 interesting signals that had not been seen before. However, further inspections of these targets did not reveal the presence of these previously hidden signals.
The authors of the study believe that their methodology may be used to speed up SETI and other data-driven surveys by applying it to other large datasets.