Erhai Zhao, Associate Professor, Department of Physics and Astronomy, is developing numerical algorithms to describe and understand superfluidity and magnetic orders in repulsively interacting Fermi gases of ultracold atoms in optical lattices. He is also employing machine learning techniques to solve quantum spin models of cold atoms.
This research is important because comprehending quantum matter consisting of many strongly interacting quantum units, such as atoms, spins, or quantum bits, remains a great challenge for researchers. It also underpins scientists’ capacity to design better materials and to solve hard problems beyond the reach of classical computers.
Zhao received $60,671 from the National Science Foundation for this project. Funding began in September 2020 and will end in late August 2023.
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