Enhancing QAOA Ansatz via Multi-Parameterized Layer and Blockwise Optimization

We propose Enhanced QAOA (EQAOA), a modified ansatz that appends a compact multi-parameter layer and uses a blockwise optimization scheme. This design preserves the QAOA evolution while broadening the candidate solution space and easing solution exploration. Applied to the MaxCut problem achieves, with an order of magnitude smaller circuit depth, approximation ratios comparable to QAOA, using a single cost–mixer layer, thus reducing gate counts by up to fivefold. Moreover, ablation studies prove that blockwise fine-tuning is crucial to deliver higher-quality solutions at shallower depth, offering a practical, quantum hardware-efficient alternative for signal processing applications.

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