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AI Starts to Sift Through String Theory's Near-Endless Possibilities
Using machine learning, string theorists are finally showing how microscopic configurations of extra dimensions translate into sets of elementary particles — though not yet those of our universe.
Using insight gathered from an assortment of computational techniques in 2019 and 2020, the group identified a handful of formulas that spit out classes of Calabi-Yau manifolds producing what they call “ broad brush ” versions of the Standard Model containing the right number of matter particles. String theorists including Anderson started trying to calculate specific metrics in these ways, but the procedures took a long time and produced overly bumpy doughnuts, which would mess up attempts to make precise particle predictions. Impressed by the ability of machines to best humans at board games, Fabian Ruehle, a physicist now at Northeastern University, wondered if similar algorithms could calculate shapes of 6D manifolds in string theory.
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