# 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…

## One Citation

The Quantum Approximate Optimization Algorithm at High Depth for MaxCut on Large-Girth Regular Graphs and the Sherrington-Kirkpatrick Model

- Physics, Computer ScienceArXiv
- 2021

Looking at random D-regular graphs, at optimal parameters and as D goes to infinity, it is found that the p = 11 QAOA beats all classical algorithms that are free of unproven conjectures.

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