Analysis of influence factors in Quantum Approximate Optimization Algorithm for Solving Max-cut Problem
Jing Wang, Junsen Lai, Meng Zhang, Fei Yao, Fang Li · 2023
In recent years, quantum algorithm research has developed rapidly, and it has become an important mode to use quantum computing cloud platform to carry out algorithm application exploration. Quantum approximate optimization algorithm can be used to solve the max-cut problem. In the process of algorithm execution, optimizer and various noise had obvious influence on the algorithm execution result. For the quantum computing simulator of HiQ platform, quantum approximate optimization algorithm was used for experimental verification, to study the types of optimizer, different noise scenarios, and the impact of noise error parameters on the maximum number of cutting edges. The prospect of quantum algorithm research was also discussed.