ETD

• max-3sat
• partitioning
• qaoa
• quantum computing
• qubo

This thesis investigates how large Max-3SAT problems can be adapted for quantum optimization by decomposing them into smaller problems that fit on current quantum hardware.To overcome qubit-count limitations, four partitioning/clustering strategies are developed to identify correlated variable groups and extract sub-QUBOs that can be solved on quantum hardware. Each subproblem is optimized and then the result for the original problem is composed by merging the suproblem solutions and applying local search for refinement. The results show that this approach preserves accuracy while enabling scalability.