• Corpus ID: 252519581

A Depth-Progressive Initialization Strategy for Quantum Approximate Optimization Algorithm

@inproceedings{Lee2022ADI,
  title={A Depth-Progressive Initialization Strategy for Quantum Approximate Optimization Algorithm},
  author={Xinwei Lee and Ning Xie and Yoshiyuki Saito and DongSheng Cai and Nobuyoshi Asai},
  year={2022}
}
The quantum approximate optimization algorithm (QAOA) is known for its capability and uni-versality in solving combinatorial optimization problems on near-term quantum devices. The results yielded by QAOA depend strongly on its initial variational parameters γ and β . Hence, parameters selection for QAOA becomes an active area of research as bad initialization might deteriorate the quality of the results, especially at great circuit depths. We first discuss the patterns of optimal parameters in… 
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