Abstract
This talk presents a control-theoretic framework for the design and analysis of quantum optimization algorithms. The central idea is to treat quantum algorithms as controlled dynamical systems, where quantum gates serve as control inputs that steer the system toward the ground or excited states of a target Hamiltonian. Building on Lyapunov-inspired feedback principles, we introduce the family of feedback-based quantum algorithms and develop new extensions addressing constrained optimization and excited state preparation. The proposed framework is motivated by the potential of these algorithms to tackle computationally challenging problems, including ground state preparation of Hamiltonians, with broad applications in engineering, chemistry, and combinatorial optimization.
Biographical Information
Rafal Wisniewski is professor and deputy head of research at the Department of Electronic Systems, Aalborg University, where he leads the Learning and Decisions Lab. An IEEE Fellow (2026) with PhD degrees in both Electrical Engineering and Mathematics, his research spans control theory, safe machine decisions, and quantum computing. He pioneered the magnetic attitude control system for Denmark's first satellite Ørsted, and his Converse Barrier Certificate Theorem is a landmark result in safety verification. He has authored over 60 journal articles and 130 conference papers, graduated 21 PhD students, and holds two patents. His recent work bridges control theory and quantum optimization. He currently serves as General Chair of the IEEE International Conference on Quantum Control, Computing and Learning (qCCL 2026).