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DAPO-QAOA: An algorithm for solving combinatorial optimization problems by dynamically constructing phase operators by Wang, Yukun; Li, ZeYang; Wan, Linchun is a scholarly article available to read on EtoBox.

What is DAPO-QAOA: An algorithm for solving combinatorial optimization problems by dynamically constructing phase operators about?

The Quantum Approximate Optimization Algorithm (QAOA) is a well-known hybrid quantum-classical algorithm for combinatorial optimization problems. Improving QAOA involves enhancing its approximation ratio while addressing practical constraints of Noisy Intermediate Scale Quantum (NISQ) devices, such as minimizing the number of two-qubit gates and reducing circuit depth. Although existing research has optimized designs for phase and mixer operators to improve performance, challenges remain, particularly concerning the excessive use of two-qubit gates in the construction of phase operators. To address these issues, we introduce a Dynamic Adaptive Phase Operator (DAPO) algorithm, which dynamically constructs phase operators based on the output of previous layers and neighborhood search approach, optimizing the problem Hamiltonian more efficiently. By using solutions generated by QAOA itself to simplify the problem Hamiltonian at each layer, the algorithm captures the problem's structural properties more effectively, progressively steering the solution closer to the optimal target. Experimental results on MaxCut and NAE3SAT problems show that DAPO achieves higher approximation ratios an

Author

Wang, Yukun; Li, ZeYang; Wan, Linchun

Published

2025

Language

EN