Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression
Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression
Hard combinatorial optimization problems, often mapped to Ising models, promise potential solutions with quantum advantage but are constrained by limited qubit counts in near-term devices. We present an innovative quantum-inspired framework that dynamically compresses large Ising models to fit available quantum hardware of different sizes. Thus, we aim to bridge …