Neural networks take on quantum entanglement

Machine learning, the field that's driving a revolution in artificial intelligence, has cemented its role in modern technology. Its tools and techniques have led to rapid improvements in everything from self-driving cars and speech recognition to the digital mastery of an ancient board game. Now, physicists are beginning to use machine learning tools to tackle a different kind of problem, one at the heart of quantum physics. In a paper published recently in Physical Review X, researchers from JQI and the Condensed Matter Theory Center (CMTC) at the University of Maryland showed that certain neural networks--abstract webs that pass information from node to node like neurons in the brain--can succinctly describe wide swathes of quantum systems . Dongling Deng, a JQI Postdoctoral Fellow who is a member of CMTC and the paper's first author, says that researchers who use computers to study quantum systems might benefit from the simple descriptions that neural networks provide.