Applications of quantum annealing in combinatorial optimization

Yarkoni, S. (2022)

Doctoral Thesis

Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinatorial optimization problems using programmable quantum hardware. In this thesis, various methods are developed and tested to understand how to formulate combinatorial optimization problems for quantum annealing. Use of both purely quantum approaches as well as hybrid quantum-classical algorithms are investigated using state-of-the-art quantum hardware. How the developed methods affect the performance of quantum hardware in practice is tested using both real-world and canonical academic problems.

• Quantum computing
• Quantum annealing
• Combinatorial optimization
• Metaheuristics

• All authors: Yarkoni, S.
• Supervisor: Bäck, T.H.W.; Plaat, A.
• Co-supervisor: Neukart, F.
• Committee: Batenburg, K.J.; Bonsangue, M.M.; Michielsen, K.; Linnhoff-Popien, C.; Wang, H.; Dunjko, V.
• Qualification: Doctor (dr.)
• Awarding Institution: Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University
• Date: 2022-12-20