SWAQ - A Quantum Annealing Simulator with Enhanced Capabilities for Specific Problems

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Quantum annealing has garnered attention for its potential to solve combinatorial optimization problems quickly. However, many combinatorial optimization problems include constraints such as selecting m items from n, which complicates balancing solution accuracy and speed. In this project, we developed a custom quantum annealing simulator that searches for solutions while consistently satisfying these constraints, and we applied and evaluated it on real-world problems.

Creator

Hayato Okada (Year: 2024 / Mentor: Kakeru Ishii)

Pitch

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