NASA: AI algorithm could help scientists find punctures in the Earth’s magnetic bubble

The first artificial intelligence algorithm that can detect when spacecraft crosses back and forth from the Earth’s magnetic field to the Sun’s could help scientists whose main goal is to find punctures in the Earth’s magnetic bubble.

A published paper describes “the first artificial intelligence algorithm” that could help scientists on the Magnetospheric Multiscale (MMS) mission team that scans data from spacecraft observations, according to a Sept. 1 press release from NASA. 

“Algorithms are mathematical instructions” that help computers learn, the article “Artificial Intelligence: How Algorithms Make Systems Smart” on the website of Wired states. 

The “Scientist in the Loop” is part of the MMS that “ensure the very best data makes it to the ground,” from spacecraft, according to the NASA press release. 

“MMS is the first big NASA mission implementing machine learning into its mission operations,” Matthew Argall, lead author of the published paper and a research scientist at the University of New Hampshire, said in the NASA press release. 

Solar wind (charged particles from the sun) collide with the Earth’s magnetic bubble. 

“The collision sites form an invisible boundary that scientists call the magnetopause,” NASA said in the press release. “By and large, the magnetopause holds strong – but not always. When conditions are right and magnetic fields align, the solar wind can puncture our magnetic bubble... The site of the breach is known as an electron diffusion region, or EDR, and finding them is the MMS mission’s primary goal.”

NASA said the new algorithm can "match" approximately 70% of judgments made by people. 

“We may be glimpsing a future where algorithms are less tools than collaborators, working alongside scientists as both learn from new data together,” NASA said in the press release.