Thesis etd-11052025-144721 |
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Thesis type
Tesi di laurea magistrale
Author
BECCARI, GIADA
URN
etd-11052025-144721
Thesis title
Partitioning Strategies for Quantum Optimization of Large MAX-3SAT Problems
Department
INGEGNERIA DELL'INFORMAZIONE
Course of study
ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING
Supervisors
relatore Cococcioni, Marco
Keywords
- max-3sat
- partitioning
- qaoa
- quantum computing
- qubo
Graduation session start date
05/12/2025
Availability
Withheld
Release date
05/12/2028
Summary
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.
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