Quantum annealing initialization of the quantum approximate optimization algorithm

@article{Sack2021QuantumAI,
  title={Quantum annealing initialization of the quantum approximate optimization algorithm},
  author={Stefan H. Sack and Maksym Serbyn},
  journal={Quantum},
  year={2021},
  volume={5},
  pages={491}
}
The quantum approximate optimization algorithm (QAOA) is a prospective near-term quantum algorithm due to its modest circuit depth and promising benchmarks. However, an external parameter optimization required in QAOA could become a performance bottleneck. This motivates studies of the optimization landscape and search for heuristic ways of parameter initialization. In this work we visualize the optimization landscape of the QAOA applied to the MaxCut problem on random graphs, demonstrating… 

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