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Quantum Algorithm Theory and Discrete Optimization Group (QAT & DOG)


Quantum computers have the potential to revolutionize how complex problems are solved. The Quantum Algorithm Theory and Discrete Optimization Group (QAT & DOG) at the University of Tennessee studies fundamental quantum algorithm design and applications of these algorithms to discrete optimization problems.

News news

  • Anthony Wilkie will be conducting research at LANL during summer 2024.
  • Dr. Herrman will be giving a talk at the NSF post-quantum AI workshop April 1-2.

Affiliated faculty

  • Dr. Rebekah Herrman
  • Dr. Jim Ostrowski
  • Dr. Bing Yao

Current students and postdoctoral researchers

  • Marzieh Bakhshi
  • Dr. Igor Gaidai
  • Moises Ponce
  • Shamim Riten
  • Anthony Wilkie
  • Mostafa Atallah

Funded Projects

  • AI TENNessee Initiative – Seed Funds for AI Research and Teambuilding: Developing ML/AI-based Tools to Analyze the Multi-dimensional Spectroscopic Data of Scanning Tunneling Microscopy (May 2023 – present)
  • NSF REU Site- Quantum algorithms and optimization (February 2023-present)
  • NSF CISE SMALL- Optimizing Quantum Circuit Design (October 2022-present)
  • DARPA ONISQ- Problem Structure and the Quantum Advantage: Theory and Algorithms (November 2019-present)
  • DOE Express-Converting quantum circuits to dynamic continuous-time quantum walks (October 2023-present)
  • DARPA IMPAQT-Analysis of feasibility of using variational quantum algorithms to solve dominating set type problems (July 2023-present)

Sample publications

  • Herrman, R., Lotshaw, P. C., Ostrowski, J., Humble, T. S., & Siopsis, G. (2022). Multi-angle quantum approximate optimization algorithm. Scientific Reports, 12(1), 6781.
  • Herrman, R., Treffert, L., Ostrowski, J., Lotshaw, P. C., Humble, T. S., & Siopsis, G. (2021). Globally optimizing QAOA circuit depth for constrained optimization problems. Algorithms, 14(10), 294.
  • Xie, J., & Yao, B. (2023). Physics-constrained deep learning for robust inverse ecg modeling. IEEE Transactions on Automation Science and Engineering, 20(1), 151.
  • Li, H., Yao, B., Tu, T., & Guo, G. (2012). Quantum computation on gate- defined semiconductor quantum dots. Chinese Science Bulletin, 57, 1919.