# A Quantum Approximate Optimization Algorithm for continuous problems

@article{Verdon2019AQA, title={A Quantum Approximate Optimization Algorithm for continuous problems}, author={Guillaume Verdon and Juan Miguel Arrazola and Kamil Br'adler and Nathan Killoran}, journal={arXiv: Quantum Physics}, year={2019} }

We introduce a quantum approximate optimization algorithm (QAOA) for continuous optimization. The algorithm is based on the dynamics of a quantum system moving in an energy potential which encodes the objective function. By approximating the dynamics at finite time steps, the algorithm can be expressed as alternating evolution under two non-commuting Hamiltonians. We show that each step of the algorithm updates the wavefunction in the direction of its local gradient, with an additional momentum…

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