(WISC.edu) The US Department of Energy recently announced the funding of another set of quantum science-driven research proposals, including that of Sau Lan Wu, Enrico Fermi professor of physics and Vilas Professor at the University of Wisconsin–Madison. With the funding, Wu and her collaborators seek to tap into the power of quantum computing to analyze the wealth of data generated by high energy physics experiments.
The title of Wu’s DOE approved project is: “Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware”.
Wu’s DOE grant marks the second to be earned by WQI members this summer. In July, Shimon Kolowitz and collaborators were awarded a grant to identify and mitigate the sources of noise that currently limit qubit performance.
For her DOE-funded project, Wu works with collaborators in quantum information science, including Miron Livny, professor of computer sciences with the Wisconsin Institute for Discovery at UW–Madison, and OpenLab of the CERN IT division. Importantly, she is also collaborating with scientists at IBM Zürich Research. Through them she has access to their quantum computer simulators and quantum computer hardware.
“Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to high energy physics with IBM’s resources,” Wu says.

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