Are we alone in the universe? It’s a question that has captivated humanity for centuries, and now, thanks to advances in machine learning, the search for extraterrestrial intelligence (SETI) is being taken to new heights. In a paper published last week in Nature Astronomy, a team of researchers led by Peter Ma of the University of Toronto shared a machine learning method for digging through data from the Breakthrough Listen project to identify signals that could be potential technosignatures — that is, indications of technological complexity that suggest an intelligent alien civilization.
Have we been contacted by aliens yet? What would it take to make a connection with an alien civilization? Could evidence of an alien civilization already exist in the data we’ve collected? In this blog post, we explore the advances in machine learning that could help answer these questions and revolutionize the search for extraterrestrial intelligence.
SETI researchers believe that any alien civilization interested in the stars would likely be looking at a particular part of the electromagnetic spectrum called narrow-band radio. This is because radio frequencies are particularly efficient for sending signals, and when we, as humans, communicate using radio waves, we use a narrow band because that’s more efficient. This section of the radio band, at around the 1420MHz range, is known as the hydrogen line and is key to studying all sorts of astronomical targets.
Ma’s research focuses on a new machine learning method for searching through this data. Instead of searching for straight lines, which indicate a signal’s presence, the researchers fed in original observations and then simulated the kind of signals they are interested in and trained their algorithm to recognize these signals. This allows a more flexible approach to signal recognition, picking up anomalies in the narrow band that flick on and off, even if they don’t have the simple line shape that the traditional algorithm would flag.
This makes the approach faster and more efficient, and it’s an important development given that SETI is essentially a numbers game. The challenge is to get enough data from enough telescopes to increase the chances of making a detection. Combing through all of that data to find the needle in the cosmic haystack requires increasingly efficient methods.
The wider field of SETI is an unusual enterprise in that researchers can dedicate their entire careers to searching for something that may or may not be out there. But even if life does exist beyond our planet, we may never have the chance to discover it. On the other hand, there’s the tantalizing possibility that humanity could detect an intriguing signal tomorrow or even that evidence of an alien civilization could already exist in the reams of data that have been collected from decades of listening to the skies.
So, as humanity becomes more and more adept at observing the universe and learning about its history, the question of whether we are alone has never been more pointed. With advances in machine learning, the search for extraterrestrial intelligence is being taken to new heights. Who knows, there might be a groundbreaking signal sitting on some hard drive in a basement right now. Someone’s got to look, right?