• Corpus ID: 239050455

Predicting parameters for the Quantum Approximate Optimization Algorithm for MAX-CUT from the infinite-size limit

@article{Boulebnane2021PredictingPF,
  title={Predicting parameters for the Quantum Approximate Optimization Algorithm for MAX-CUT from the infinite-size limit},
  author={Sami Boulebnane and Ashley Montanaro},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.10685}
}
Combinatorial optimization is regarded as a potentially promising application of near and long-term quantum computers. The best-known heuristic quantum algorithm for combinatorial optimization on gate-based devices, the Quantum Approximate Optimization Algorithm (QAOA), has been the subject of many theoretical and empirical studies. Unfortunately, its application to specific combinatorial optimization problems poses several difficulties: among these, few performance guarantees are known, and… 
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