Quantum algorithms for combinatorial optimization

Quantum computing has the potential to revolutionize how difficult optimization problems are solved, however current quantum devices are limited by the number of quantum bits and architecture. In the near-term it is critical to determine how to integrate classical techniques into quantum algorithms in order to solve relevant, currently intractable problems. This talk will discuss recent results in the intersection of classical optimization techniques, graph theory, the quantum approximate optimization algorithm and on quantum walks on graphs.

Rebekah Herrman

The University of Tennessee, Knoxville on September 1, 2023 at 10:15 AM in EB3 2207
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Dr. Rebekah Herrman is an Assistant Professor in the Industrial and Systems Engineering department at the University of Tennessee Knoxville (UTK). She received her Ph.D. in mathematics in 2020 from the University of Memphis with a focus in combinatorics. While there, she studied graph theory games and optimization problems on graphs. She is a class of 2022 DARPA FORWARD Riser, advisor to the UTK chapter of Graduate Society of Women Engineers, and is an associate editor of Springer Quantum Information Processing. Her work is supported by the National Science Foundation, Department of Energy, and DARPA. Aside from graph games, her current research interest lies in the intersection of quantum algorithms, combinatorial optimization problems, and graph theory.

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