Tesi etd-11052025-144721 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
BECCARI, GIADA
URN
etd-11052025-144721
Titolo
Partitioning Strategies for Quantum Optimization of Large MAX-3SAT Problems
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING
Relatori
relatore Cococcioni, Marco
Parole chiave
- max-3sat
- partitioning
- qaoa
- quantum computing
- qubo
Data inizio appello
05/12/2025
Consultabilità
Non consultabile
Data di rilascio
05/12/2028
Riassunto
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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