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