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Sampled-Based Guided Quantum Walk: Non-variational quantum algorithm for combinatorial optimization
We introduce SamBa-GQW, a novel quantum algorithm for solving binary combinatorial optimization problems of arbitrary degree with no use of any classical optimizer. The algorithm is based on a continuous-time quantum walk on the solution space represented as a graph. The walker explores the solution
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