In 2015, the same year an immense observatory on Earth captured proof of the 4D fabric of spacetime, scientists began toying with a rather far-fetched idea: If intelligent aliens are out there, might they have tried making a scientific megastructure of their own? And if they did, can we find it? Actually, have we already?
Enlisting The Machines
In short, Giles and his team intend to search for the confusing, mysterious, intriguing, and starkly out-of-the-ordinary signals in data collected by NASA’s Transiting Exoplanet Survey Satellite, or TESS. They want to hunt for starlight dips that don’t have a defined shape, a defined depth or even a defined timeframe. The cosmic outliers. Strange dips like these can be spotted through photometric curves, which represent brightness over time. “We’re counting photons,” Giles explained in a nutshell. The kicker, however, is precisely how the team wishes to embark on this anomaly-hunting quest: Machine learning.
The process is pretty much as follows. TESS data used in the study is based on the satellite’s view of different sky sectors. These sectors were viewed across some 30 days at a time; during that scan, TESS took a snapshot of the observed area once every 30 minutes. This eventually led the team to about 60 million light curves ready for analysis, generated for stars brighter than 14 magnitude. In the magnitude system, smaller numbers are brighter than larger numbers — a magnitude 0 object is 100 times brighter than a magnitude 5 object, for instance. A full moon goes into the negatives with a magnitude of around -12.6; the sun shines around magnitude -27. And so on.
The next step is to start mass organizing the light curves based on things like their shapes and periodicities. “We’re processing 60 million different light curves so we need them to be cheap and easy to calculate,” Giles said. “We calculate these cheap metrics and then we run the anomaly detection on it, and this is a density based anomaly detection — we find out what has features that stick out.”
Finding An Alien
To be perfectly honest, I was thrilled to hear something intrinsically human can find strange things like no machine really can. I think it grounds our admittedly wild endeavor of trying to locate intelligent aliens. We’re inherently curious I suppose, and somehow drawn to lapses in patterns.
“There’s a certain level to which we can use ML methods,” Giles told Space.com, “but ultimately, we need to be able to understand why it is things are happening.”
Maybe a pool full of even the most highly accurate datasets is just that — a pool full of highly accurate datasets — until a human starts parsing through to make connections a machine hasn’t yet been programmed to recognize.
“For things like anomaly detection, there’s an additional trick,” Giles said. “There’s not a ground truth, so we can’t train something necessarily to find the weirdest stuff, or the stuff that’s the most interesting, because we don’t necessarily know what that’s going to be.”
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Source: Space
