講演情報
[17a-K306-7]Parameters Optimization for Ising Spin Computing by Simulated Quantum Annealing Combined with Extraction-Type Majority Voting Logic
〇Yu Zhao1, Koki Awaya1, Ryoya Yonemoto1, Moe Shimada1, Jun-ichi Shirakashi1 (1.Tokyo Univ. Agr. and Tech.)
キーワード：
Ising Machine、Simulated Quantum Annealing、Combinatorial Optimization Problems
The combinatorial optimization problem is central to many real-world challenges. Quantum annealing and quantum-inspired technologies, particularly quantum-inspired Ising machines, offer efficient solutions to large-scale problems by overcoming quantum hardware limitations. This paper introduces a hybrid approach combining Extraction-Type Majority Voting Logic (E-MVL) with Simulated Quantum Annealing (SQA). E-MVL aids in efficiently searching the ground state of the Ising spin model by adjusting spin-spin interaction sparsity, enabling controlled energy increases. The integration of E-MVL into SQA is examined and compared with Simulated Annealing (SA) to optimize parameters and improve performance.