AI reveals new physics in dusty plasma

Physicists used a machine-learning method to identify surprising new twists on the non-reciprocal forces governing a many-body system.

The journal PNAS published the findings by experimental and theoretical physicists at Emory University, based on a neural network model and data from laboratory experiments on dusty plasma — ionized gas containing suspended dust particles. 

The work is one of the relatively few instances of using AI not as a data processing or predictive tool, but to discover new physical laws governing the natural world.

"We showed that we can us AI to discover new physics," says Justin Burton, an Emory professor of experimental physics and senior co-author of the paper. "Our AI method is not a black box: we understand how and why it works. The framework it provides is also universal. It could potentially be applied to other many-body systems to open to new routes to discovery."

Evolving views: A new look at the Scopes Trial

Emory professor of psychology Harold Gouzoules, left, and his son Alexander Gouzoules, an Emory alum who is a legal scholar.

A combination of inherited genes and life experiences led Alexander Gouzoules (a legal scholar) and his father, Harold Gouzoules (an evolutionary biologist), to co-author a book about the 1925 Scopes trial. 

“The Hundred Years’ Trial: Law, Evolution, and the Long Shadow of Scopes v. Tennessee” blends their expertise. Johns Hopkins University Press published the book, marking the centenary of the fierce, public legal battle over the right to teach evolution in a Tennessee high school. 

“We had the ideal meshing of interests to take on the topic in a new way,” says Harold Gouzoules, an Emory professor of psychology who studies the evolution of primate social behavior. “I took on the science and Alex covered the legal ramifications of the trial.”

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