Sampled-Based Guided Quantum Walk: Non-variational quantum algorithm for combinatorial optimization
SamBa–GQW is a new quantum algorithm for solving complex binary optimization problems without needing a classical optimizer. It uses an offline classical sampling protocol to estimate the problem's Hamiltonian spectrum, which then guides a continuous-time quantum walk. This approach avoids scaling issues and barren plateaus found in older methods, achieving high-quality approximate solutions efficiently.