Machine learning could aid efforts to answer long-standing astrophysical questions | Science & Technology

In an ongoing game of cosmic hide and seek, scientists have a new tool that may give them an edge. Physicists at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) have developed a computer program incorporating machine learning that could help identify blobs of plasma in outer space known as plasmoids. In a novel twist, the program has been trained using simulated data.

The program will sift through reams of data gathered by spacecraft in the magnetosphere, the region of outer space strongly affected by Earth’s magnetic field, and flag telltale signs of the elusive blobs. Using this technique, scientists hope to learn more about the processes governing magnetic reconnection, a process that occurs in the magnetosphere and throughout the universe that can damage communications satellites and the electrical grid.

Scientists believe that machine learning could improve plasmoid-finding capability, aid the basic understanding of magnetic reconnection and allow researchers to better prepare for the aftermath of reconnection-caused disturbances.

“As far as we know, this is the first time that anyone has used artificial intelligence trained on simulated data to look for plasmoids,” said Kendra Bergstedt, a graduate student in the Princeton Program in Plasma Physics, which is based at PPPL. Bergstedt was the first author of the paper reporting the results in Earth and Space Science. The work pairs the Lab’s growing expertise in computational sciences with its long history of exploring magnetic reconnection.

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Scientists want to find reliable, accurate methods for detecting plasmoids so they can determine whether they affect magnetic reconnection, a process consisting of magnetic field lines separating, violently reattaching and releasing tremendous amounts of energy. When it occurs near Earth, reconnection can trigger a cascade of charged particles falling into the atmosphere, disrupting satellites, mobile phones and the…

Source www.sciencedaily.com

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