Space and astronomy news
Plenty of recent mainstream news articles have touted AI’s ability to assist in the process of scientific discovery. But most of them predicted that it could take years or even decades to see the full effect. Astronomy seems ahead of the curve, though, with the announcement of a new AI system developed by researchers at Northwestern University and elsewhere that can now autonomously detect and classify supernovae.
BTSbot’s work is simple – crawling through massive databases, looking for a bright point of light that wasn’t there before. Those bright points represent one of the most fantastical of all astronomical phenomena – supernovae. And typically, it’s a herculean manual effort to find them.
Luckily, BTSbot doesn’t get bored, so it is well-placed to do that trawling. But it’s also well placed to integrate into some automated infrastructure already in the supernovae hunting community. To understand how it’s probably easiest to talk through BTSbot’s first discovery of a supernova – though admittedly, the supernova it found, known as SN2023tyk, had already been found via the traditional manual search as well.
SNIascore’s specialty is determining what kind of supernova an explosion was. It analyzes the spectra provided by both ZTF and Palomar and compares them to known values of other types of supernovae. It is not terribly tricky statistically, but it is still an impressive process when combined with the automated capture and analysis steps that came before it.
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