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Quantum Approximate Optimization Algorithm (scipy implementation)

warning: this project is under development, think before using it.

Code is base on QAOA paper, Farhi, E., Goldstone, J., & Gutmann, S. (2014). A Quantum Approximate Optimization Algorithm. Code is partly referenced from minimum vertex cover problem project.

Features:

  • max-cut problem and vertex cover problem,
  • improved performance (with respect to Vertex-Cover-QAOA),
  • general purposed,
  • projectq support.

To Run Tests

$ cd qaoa
$ ./ui.py mc   # training max cut problem
$ ./ui.py vc   # training vertex cover problem

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