Quantum dropout: On and over the hardness of quantum approximate optimization algorithm
Zhenduo Wang, Pei-Lin Zheng, Biao Wu, Yi Zhang
Abstract
A combinatorial optimization problem becomes very difficult in situations where the energy landscape is rugged, and the global minimum locates in a narrow region of the configuration space. When using the quantum approximate optimization algorithm (QAOA) to tackle these harder cases, we find that difficulty mainly originates from the QAOA quantum circuit instead of the cost function. To alleviate the issue, we selectively drop the clauses defining the quantum circuit while keeping the cost function intact. Due to the combinatorial nature of the optimization problems, the dropout of clauses in the circuit does not affect the solution. Our numerical results confirm improvements in QAOA's performance with various types of quantum-dropout implementations.